Items where Subject is "C53 - Forecasting and Prediction Methods ; Simulation Methods"

Arabic

CHIKHI, Mohamed and Benguesmi, Tarek (2013): تحليل سلوك مبيعات الكهرباء الموجه للقطاع العائلي في ظل وجود التقلبات الموسمية باستخدام نماذج SARIMA.

Azerbaijani

Mehdiyev, Mehdi and Ahmadov, Vugar and Huseynov, Salman and Mammadov, Fuad (2015): Ölkə iqtisadiyyatı üzrə göstəricilərin modelləşdirilməsi və proqnozlaşdırılması: problemlər və praktiki çətinliklər.

English

AMMOURI, Bilel and TOUMI, Hassen and ISSAOUI, Fakhri and ZITOUNA, Habib (2015): Forecasting Inflation in Tunisia into instability: Using Dynamic Factors Model a two-step based on Kalman filtering.

Abdullah, Muhammad and Gul, Zarro and Waseem, Faiza and Islam, Tanweer (2021): The State of Pakistan’s Economy and the Ineffectiveness of Monetary Policy.

Abounoori, Abbas Ali and Naderi, Esmaeil and Gandali Alikhani, Nadiya and Amiri, Ashkan (2013): Financial Time Series Forecasting by Developing a Hybrid Intelligent System. Published in: European Journal of Scientific Research , Vol. 98, No. 4 (4 March 2013): pp. 10-20.

Abounoori, Abbas Ali and Naderi, Esmaeil and Gandali Alikhani, Nadiya and Amiri, Ashkan (2013): Financial Time Series Forecasting by Developing a Hybrid Intelligent System. Published in: European Journal of Scientific Research , Vol. 98, No. 4 (4 March 2013): pp. 529-541.

Adekunle, Wasiu and Bekoe, William and Badmus, Sheriff and Anagun, Michael and Alimi, Wasiu (2021): Nexus Between Fiscal Discipline And The Budget Process In Africa: Evidence From Nigeria.

Adeniyi, Isaac Adeola (2020): Bayesian Generalized Linear Mixed Effects Models Using Normal-Independent Distributions: Formulation and Applications. Forthcoming in: AStA-Advances in Statistical Analysis

Ahec Šonje, Amina and Katarina, Bacic (2006): A composite leading indicator for a small transition economy: the case of Croatia.

Ahmadzadeh Mashinchi, Sina (2010): The impact of the global economic crisis on non-oil operations of ports in Iran. Published in: Middle East Journal of Scientific Research (ISI Indexed) , Vol. 9, No. 5 (15 November 2011): pp. 596-601.

Ahoniemi, Katja and Lanne, Markku (2007): Joint Modeling of Call and Put Implied Volatility. Published in:

Ahumada, Hildegart and Espina, Santos and Navajas, Fernando H. (2020): COVID-19 with uncertain phases: estimation issues with an illustration for Argentina.

Aknouche, Abdelhakim and Gouveia, Sonia and Scotto, Manuel (2023): Random multiplication versus random sum: auto-regressive-like models with integer-valued random inputs.

Aknouche, Abdelhakim and Dimitrakopoulos, Stefanos (2020): On an integer-valued stochastic intensity model for time series of counts.

Aknouche, Abdelhakim and Francq, Christian (2019): Two-stage weighted least squares estimator of the conditional mean of observation-driven time series models.

Albers, Scott (2013): Foundations of the economic and social history of the United States: Apologia.

Albers, Scott (2013): Foundations of the economic and social history of the United States: Metaphysical.

Albers, Scott (2012): Predicting crises: Five essays on the mathematic prediction of economic and social crises. Published in: Middle East Studies On-line Journal , Vol. Volume, No. Issue 6 (8 August 2011): pp. 199-253.

Albers, Scott and Albers, Andrew L. (2013): Does “Okun’s Law” state a Pi:1 ratio? Toward a harmonic interpretation of why Okun’s Law works.

Albers, Scott and Albers, Andrew L. (2011): The Golden Mean, the Arab Spring and a 10-step analysis of American economic history. Published in: The Middle East Studies Online Journal , Vol. 3, No. 6 (3 August 2011): pp. 199-253.

Albers, Scott and Albers, Andrew L. (2012): On the mathematic prediction of economic and social crises: toward a harmonic interpretation of the Kondratiev wave.

Albu, Lucian-Liviu (2003): Estimating contribution of factors to long-term growth in Romania. Published in: Revue Roumaine des Sciences Economiques , Vol. 48, No. 2 : pp. 197-206.

Albu, Lucian-Liviu and Roudoi, Andrei (2003): Scenarios of economic development in Romania - medium to long-term forecasting models. Published in: Romanian Journal of Economic Forecasting , Vol. 4, No. 5 (December 2003): pp. 64-77.

Albulescu, Claudiu Tiberiu (2009): Forecasting credit growth rate in Romania: from credit boom to credit crunch?

Aliyu, Shehu Usman Rano and Aminu, Abubakar Wambai (2018): Economic regimes and stock market performance in Nigeria: Evidence from regime switching model.

Alper, C. Emre and Fendoglu, Salih and Saltoglu, Burak (2008): Forecasting Stock Market Volatilities Using MIDAS Regressions: An Application to the Emerging Markets.

Amiri, Arshia and Bakhshoodeh, Mohamad and Najafi, Bahaeddin (2011): Forecasting seasonality in prices of potatoes and onions: challenge between geostatistical models, neuro fuzzy approach and Winter method.

Amiri, Arshia and Ventelou, Bruno (2011): Forecasting the role of public expenditure in economic growth Using DEA-neural network approach.

Anastasiou, Dimitris and Drakos, Konstantinos and Kapopoulos, Panayotis (2022): Predicting international tourist arrivals in Greece with a novel sector-specific business leading indicator.

Andres, Antonio Rodriguez and Otero, Abraham and Amavilah, Voxi Heinrich (2021): Evaluation of technology clubs by clustering: A cautionary note. Forthcoming in: Applied Economics (2021)

Andres, Antonio Rodriguez and Otero, Abraham and Amavilah, Voxi Heinrich (2021): Using Deep Learning Neural Networks to Predict the Knowledge Economy Index for Developing and Emerging Economies. Published in: Expert Systems with Applications , Vol. 184, No. https://doi.org/10.1016/j.eswa.2021.115514 (1 December 2021)

Andrianady, Josué R. (2023): Crunching the Numbers: A Comparison of Econometric Models for GDP Forecasting in Madagascar.

Andrianady, Josué R. (2023): Comparing Econometric Models for Forecasting GDP in Madagascar.

Andriantomanga, Zo (2023): The role of survey-based expectations in real-time forecasting of US inflation.

Andrle, Michal (2008): The Role of Trends and Detrending in DSGE Models.

Angelidis, Timotheos and Benos, Alexandros and Degiannakis, Stavros (2007): A Robust VaR Model under Different Time Periods and Weighting Schemes. Published in: Review of Quantitative Finance and Accounting , Vol. 2, No. 28 (2007): pp. 187-201.

Angelidis, Timotheos and Benos, Alexandros and Degiannakis, Stavros (2004): The Use of GARCH Models in VaR Estimation. Published in: Statistical Methodology , Vol. 2, No. 1 (2004): pp. 105-128.

Angelidis, Timotheos and Degiannakis, Stavros (2005): Modeling Risk for Long and Short Trading Positions. Published in: Journal of Risk Finance , Vol. 3, No. 6 (2005): pp. 226-238.

Angelidis, Timotheos and Degiannakis, Stavros (2008): Volatility forecasting: Intra-day versus inter-day models. Published in: Journal of International Financial Markets Institutions and Money No. 18 (2008): pp. 449-465.

Angelidis, Timotheos and Degiannakis, Stavros (2008): Volatility forecasting: intra-day vs. inter-day models. Published in: Journal of International Financial Markets Institutions and Money No. 18 (2008): pp. 449-465.

Ardakani, Omid and Kishor, N. Kundan (2014): Examining the Success of the Central Banks in Inflation Targeting Countries: The Dynamics of Inflation Gap and the Institutional Characteristics.

Ardia, David and Dufays, Arnaud and Ordás Criado, Carlos (2023): Linking Frequentist and Bayesian Change-Point Methods.

Ardic, Oya Pinar and Ergin, Onur and Senol, G. Bahar (2008): Exchange Rate Forecasting: Evidence from the Emerging Central and Eastern European Economies.

Ari, Ali (2008): An Early Warning Signals Approach for Currency Crises: The Turkish Case.

Armstrong, J. Scott (1978): Forecasting with Econometric Methods: Folklore Versus Fact. Published in: Journal of Business No. 51 (1978): pp. 549-564.

Armstrong, J. Scott (1988): Review of Ravi Batra, The Great Depression of 1990. Published in: International Journal of Forecasting No. 4 (1988): pp. 493-495.

Armstrong, J. Scott (1983): Strategic Planning and Forecasting Fundamentals.

Armstrong, J. Scott and Brodie, Roderick J. (1999): Forecasting for Marketing. Published in: Quantitative Methods in Marketing : pp. 92-120.

Armstrong, J. Scott and C., Michael (1972): A Comparative Study of Methods for Long-Range Market Forecasting. Published in: Management Science No. 19 (1972): pp. 211-221.

Armstrong, J. Scott and Graefe, Andreas (2009): Predicting Elections from Biographical Information about Candidates.

Armstrong, J. Scott and Green, Kesten C. and Jones, Randall J. and Wright, Malcolm (2008): Predicting elections from politicians’ faces.

Armstrong, J. Scott and Green, Kesten C. and Soon, Willie (2007): Polar Bear Population Forecasts: A Public-Policy Forecasting Audit.

Arnold, Rob (2023): Uniform Confidence/Certainty Estimation.

Arnold Cote, K. Nicole and Smith, Wm. Doyle and Fullerton, Thomas M., Jr. (2010): Municipal Non-Residential Real Property Valuation Forecast Accuracy. Published in: International Journal of Business & Economics Perspectives , Vol. 6, No. 1 (22 March 2011): pp. 56-77.

Arora, Vipin (2013): Comparisons of Chinese and Indian Energy Consumption Forecasting Models.

Asante Gyamerah, Samuel and Ngare, Philip and Ikpe, Dennis (2018): A Levy Regime-Switching Temperature Dynamics Model for Weather Derivatives. Published in: International Journal of Stochastic Analysis , Vol. 2018, No. 8534131 (10 June 2018): pp. 1-16.

Asongu, Simplice (2014): On foreign aid distortions to governance.

Asongu, Simplice and Nnanna, Joseph (2019): Foreign aid, instability and governance in Africa. Published in: Politics & Policy , Vol. 44, No. 4 (August 2019): pp. 807-848.

Asongu, Simplice and Nwachukwu, Jacinta (2016): Is the Threat of Foreign Aid Withdrawal an Effective Deterrent to Political Oppression? Evidence from 53 African Countries. Forthcoming in: Journal of Economic Issues

Asongu, Simplice A and Nwachukwu, Jacinta C. (2015): Foreign aid instability and bundled governance dynamics in Africa.

Athanasopoulos, George and Hyndman, Rob J. and Kourentzes, Nikolaos and Petropoulos, Fotios (2015): Forecasting with Temporal Hierarchies.

Ayub, Mehar (1998): A simulation model of corporate finances: A study of the companies listed on Karachi stock exchange. Published in: Conference Proceedings, International Institute of Forecasting, Georgia Institute of Technology, Atlanta (2001) , Vol. 1, No. 2001 (2001): pp. 1-55.

BLINOV, Sergey (2017): Economic Forecasting Based on the Relationship between GDP and Real Money Supply.

Bakker, Bas and Ghazanchyan, Manuk and Ho, Alex and Nanda, Vibha (2020): The Lack of Convergence of Latin-America Compared with CESEE: Is Low Investment to Blame?

Balli, Faruk and Elsamadisy, Elsayed (2010): Modelling the Currency in Circulation for the State of Qatar.

Bandyopadhyay, Arindam (2007): Credit Risk Models for Managing Bank’s Agricultural Loan Portfolio.

Bandyopadhyay, Arindam (2007): Credit Risk Models for Managing Bank’s Agricultural Loan Portfolio.

Barnett, William and Chauvet, Marcelle and Leiva-Leon, Danilo and Su, Liting (2016): Nowcasting nominal gdp with the credit-card augmented Divisia monetary aggregates.

Barnett, William and Chauvet, Marcelle and Leiva-Leon, Danilo and Su, Liting (2016): The credit-card-services augmented Divisia monetary aggregates.

Barnett, William and Ghosh, Taniya (2013): Bifurcation Analysis of an Endogenous Growth Model.

Barnett, William and Park, Sohee (2021): Forecasting Inflation and Output Growth with Credit-Card-Augmented Divisia Monetary Aggregates.

Barnett, William and Su, Liting (2016): Risk adjustment of the credit-card augmented Divisia monetary aggregates.

Bartolucci, Francesco and Pennoni, Fulvia and Vittadini, Giorgio (2015): Causal latent Markov model for the comparison of multiple treatments in observational longitudinal studies.

Bastianin, Andrea and Galeotti, Marzio and Manera, Matteo (2016): Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers.

Bastos, João A. (2019): Forecasting the capacity of mobile networks. Forthcoming in: Telecommunication Systems

Bazhenov, Timofey and Fantazzini, Dean (2019): Forecasting Realized Volatility of Russian stocks using Google Trends and Implied Volatility. Published in: Russian Journal of Industrial Economics , Vol. 1, No. 12 (2019): pp. 79-88.

Beja Jr., Edsel (2014): Income growth and happiness: Reassessment of the Easterlin Paradox.

Beneki, Christina and Eeckels, Bruno and Leon, Costas (2009): Signal Extraction and Forecasting of the UK Tourism Income Time Series. A Singular Spectrum Analysis Approach.

Benkovskis, Konstantins (2005): Econometric analysis and forecasting of Latvia's balance of payments.

Bentour, El Mostafa (2013): Oil prices, drought periods and growth forecasts in Morocco. Published in: International Journal of Economics and Management Science , Vol. 3, No. 1 (22 February 2014): pp. 1-12.

Bentour, El Mostafa (2015): A ranking of VAR and structural models in forecasting.

Berg, Tim Oliver (2015): Multivariate Forecasting with BVARs and DSGE Models.

Bersimis, Sotirios and Degiannakis, Stavros and Georgakellos, Dimitrios (2017): Real Time Monitoring of Carbon Monoxide Using Value-at-Risk Measure and Control Charting. Published in: Journal of Applied Statistics , Vol. 1, No. 44 (2017): pp. 89-118.

Berster, Peter and Gelhausen, Marc Christopher and Wilken, Dieter (2009): Business Aviation in Germany: An empirical and model-based analysis. Published in: Proceedings of the 13th Air Transport Research Society (ATRS) World Conference 2009 in Abu Dhabi, United Arab Emirates (2009): pp. 1-19.

Bespalova, Olga (2018): Forecast Evaluation in Macroeconomics and International Finance. Ph.D. thesis, George Washington University, Washington, DC, USA.

Bessler, David and Kibriya, Shahriar and Chen, Junyi and Price, Ed (2014): On Forecasting Conflict in Sudan: 2009-2012.

Bessonovs, Andrejs (2011): GDP Modelling with Factor Model: an Impact of Nested Data on Forecasting Accuracy.

Bezemer, Dirk J (2009): “No One Saw This Coming”: Understanding Financial Crisis Through Accounting Models.

Bhadury, Soumya and Ghosh, Saurabh and Gopalakrishnan, Pawan (2021): In quest for policy 'silver bullets' towards triggering a v-shaped recovery.

Bhadury, Soumya and Ghosh, Saurabh and Kumar, Pankaj (2019): Nowcasting GDP Growth Using a Coincident Economic Indicator for India.

Bhatt, Vipul and Kishor, Kundan and Marfatia, Hardik (2017): Estimating excess sensitivity and habit persistence in consumption using Greenbook forecast as an instrument.

Bianchi, Carlo and Brillet, Jean-Louis and Calzolari, Giorgio (1985): Effectiveness versus reliability of policy actions under government budget constraint: the case of France.

Bianchi, Carlo and Brillet, Jean-Louis and Calzolari, Giorgio (1986): Forecasts and constraints on policy actions: the reliability of alternative instruments.

Bianchi, Carlo and Brillet, Jean-Louis and Calzolari, Giorgio (1988): A trade-off criterion for evaluating effectiveness and reliability of alternative policy actions. Published in: Atti del Dodicesimo Convegno A.M.A.S.E.S. No. Palermo, 14-16 Settembre 1988 (14 September 1988): pp. 185-217.

Bianchi, Carlo and Brillet, Jean-Louis and Calzolari, Giorgio and Panattoni, Lorenzo (1987): Forecast variance in simultaneous equation models: analytic and Monte Carlo methods. Published in: INSEE, Paris, France No. Paper presented at the Seminaire d'Econometrie de Malinvaud (February 1987): pp. 1-19.

Bianchi, Carlo and Calzolari, Giorgio (1982): Evaluating forecast uncertainty due to errors in estimated coefficients: empirical comparison of alternative methods. Published in: Evaluating the reliability of macro-economic models No. Ed. by G.C.Chow and P.Corsi, John Wiley & Sons, Ltd. (1982): pp. 251-277.

Bianchi, Carlo and Calzolari, Giorgio (1979): Simulation of a nonlinear econometric model. Published in: Simulation of Systems '79, ed. by L. Dekker, G. Savastano, and G. C. Vansteenkiste (1980): pp. 105-113.

Bianchi, Carlo and Calzolari, Giorgio (1983): Standard errors of forecasts in dynamic simulation of nonlinear econometric models: some empirical results. Published in: Time Series Analysis: Theory and Practice, ed. by O.D.Anderson No. Amsterdam: North Holland (1983): pp. 177-198.

Bianchi, Carlo and Calzolari, Giorgio and Cleur, Eugene M. (1978): Spectral analysis of stochastic and analytic simulation results for a nonlinear model for the Italian economy. Published in: Compstat 1978, Proceedings in Computational Statistics No. Ed. by L. C. A. Corsten, and J. Hermans. Vienna: Physica Verlag (1978): pp. 348-354.

Bianchi, Carlo and Calzolari, Giorgio and Cleur, Eugene M. and Gambetta, Guido and Stagni, Anna and Sterbenz, Frederic (1978): Stochastic simulation and dynamic properties of the new version of the Italian model.

Bianchi, Carlo and Calzolari, Giorgio and Corsi, Paolo (1976): Monte Carlo methods in econometrics: a package for the stochastic simulation. Published in: Paper presented at the Congres Europeen des Statisticiens. Universite Scientifique et Medicale de Grenoble, (September 1976): pp. 1-10.

Bianchi, Carlo and Calzolari, Giorgio and Corsi, Paolo (1979): On the restricted reduced form of the Klein-I model: revised computations to complete "A note on the numerical results by Goldberger, Nagar and Odeh", Econometrica, 47 (1979). Published in: IBM Italy Technical Report No. G513-3575 (May 1979): pp. 1-17.

Bianchi, Carlo and Calzolari, Giorgio and Corsi, Paolo (1976): Simulation properties of alternative methods of estimation: an application to a model of the Italian economy. Published in: Compstat 1976, Proceedings in Computational Statistics No. Ed. by J. Gordesch, and P. Naeve. Vienna: Physica Verlag (1976): pp. 407-415.

Bianchi, Carlo and Calzolari, Giorgio and Corsi, Paolo (1979): Some results on the stochastic simulation of a nonlinear model of the Italian economy. Published in: Models and Decision Making in National Economies No. ed. by J. M. L. Janssen, L. F. Pau, and A. Straszak. Amsterdam: North-Holland (1979): pp. 411-418.

Bianchi, Carlo and Calzolari, Giorgio and Corsi, Paolo (1981): Standard errors of multipliers and forecasts from structural coefficients with block-diagonal covariance matrix. Published in: Dynamic Modelling and Control of National Economies (IFAC) No. Ed. by J. M. L. Janssen, L. F. Pau, and A. J. Straszak. Oxford: Pergamon Press (1981): pp. 311-316.

Bianchi, Carlo and Calzolari, Giorgio and Corsi, Paolo (1979): A package for analytic simulation of econometric models. Published in: Optimization Techniques: Proceedings of the 9th IFIP Conference on Optimization Techniques. Warsaw, September 4-8, 1979 (September 1980): pp. 404-413.

Bianchi, Carlo and Calzolari, Giorgio and Weihs, Claus (1986): Parametric and nonparametric Monte Carlo estimates of standard errors of forecasts in econometric models.

Bilgili, Faik and Doğan, İbrahim and H. Tülüce, Nadide and Kuşkaya, Sevda (2014): The impact of biomass, geothermal and hydroelectric energy consumption on industrial production: A threshold cointegration model with regime shifts.

Bisio, Laura and Moauro, Filippo (2017): Temporal disaggregation by dynamic regressions: recent developments in Italian quarterly national accounts. Forthcoming in: Statistica Neerlandica

Boer, Lukas and Pescatori, Andrea and Stuermer, Martin (2021): Energy Transition Metals.

Bonga-Bonga, Lumengo and Mwamba, Muteba (2015): A multivariate model for the prediction of stock returns in an emerging market: A comparison of parametric and non-parametric models.

Bonino-Gayoso, Nicolás and García-Hiernaux, Alfredo (2019): TF-MIDAS: a new mixed-frequency model to forecast macroeconomic variables.

Bovi, Maurizio (2019): A Time-Varying Expectations Formation Mechanism. Published in: Economia Politica No. 4 (December 2019)

Bradrania, Reza and Pirayesh Neghab, Davood (2021): State-dependent asset allocation using neural networks. Published in: European Journal of Finance , Vol. 28, No. 11 (12 August 2021): pp. 1130-1156.

Brahmana, Rayenda Khresna (2022): Do Machine Learning Approaches Have the Same Accuracy in Forecasting Cryptocurrencies Volatilities?

Branimir, Jovanovic and Magdalena, Petrovska (2010): Forecasting Macedonian GDP: Evaluation of different models for short-term forecasting. Published in: National Bank of the Republic of Macedonia Working Paper (August 2010)

Breitenstein, Miriam and Anke, Carl-Philipp and Nguyen, Duc Khuong and Walther, Thomas (2019): Stranded Asset Risk and Political Uncertainty: The Impact of the Coal Phase-out on the German Coal Industry.

Brkic, Sabina and Hodzic, Migdat and Dzanic, Enis (2017): Fuzzy Logic Model of Soft Data Analysis for Corporate Client Credit Risk Assessment in Commercial Banking. Forthcoming in: Fifth Scientific Conference with International Participation “Economy of Integration” ICEI 2017 (December 2017)

Brkic, Sabina and Hodzic, Migdat and Dzanic, Enis (2018): Soft Data Modeling via Type 2 Fuzzy Distributions for Corporate Credit Risk Assessment in Commercial Banking. Forthcoming in:

Bruno, Giancarlo (2012): Consumer confidence and consumption forecast: a non-parametric approach.

Bruno, Giancarlo (2008): Forecasting Using Functional Coefficients Autoregressive Models.

Bruno, Giancarlo (2009): Non-linear relation between industrial production and business surveys data.

Bruno, Giancarlo and Lupi, Claudio (2003): Forecasting Euro-Area Industrial Production Using (Mostly) Business Surveys Data.

Bucci, Andrea (2019): Cholesky-ANN models for predicting multivariate realized volatility.

Bucci, Andrea (2017): Forecasting realized volatility: a review.

Bucci, Andrea (2019): Realized Volatility Forecasting with Neural Networks.

Buncic, Daniel (2009): Understanding forecast failure in ESTAR models of real exchange rates.

Buncic, Daniel (2009): Understanding forecast failure of ESTAR models of real exchange rates.

Buncic, Daniel (2008): A note on long horizon forecasts of nonlinear models of real exchange rates: Comments on Rapach and Wohar (2006).

Buss, Ginters (2010): A note on GDP now-/forecasting with dynamic versus static factor models along a business cycle.

Bušs, Ginters (2009): Comparing forecasts of Latvia's GDP using simple seasonal ARIMA models and direct versus indirect approach.

Bušs, Ginters (2009): Economic forecasts with Bayesian autoregressive distributed lag model: choosing optimal prior in economic downturn.

Bušs, Ginters (2010): Forecasts with single-equation Markov-switching model: an application to the gross domestic product of Latvia.

Byrne, Joseph P and Korobilis, Dimitris and Ribeiro, Pinho J (2014): Exchange Rate Predictability in a Changing World.

Byrne, Joseph P and Korobilis, Dimitris and Ribeiro, Pinho J (2014): On the Sources of Uncertainty in Exchange Rate Predictability.

Bystrov, Victor (2013): A factor-augemented model of markup on mortgage loans in Poland.

CERQUA, AUGUSTO and LETTA, MARCO (2020): Local economies amidst the COVID-19 crisis in Italy: a tale of diverging trajectories.

Cadogan, Godfrey (2010): Forecasting The Pricing Kernel of IBNR Claims Development In Property-Casualty Insurance.

Cadogan, Godfrey (2010): Modeling And Forecasting Imported Japanese Parts Content Of US Transplants: An Error Correction And State Space Approach.

Caiado, Jorge (2004): Modelling and forecasting the volatility of the portuguese stock index PSI-20. Published in: Portuguese Journal of Management Studies , Vol. XI, No. Nº1 (2004): pp. 3-21.

Caiado, Jorge (2004): Modelling and forecasting the volatility of the portuguese stock index PSI-20. Published in: Portuguese Journal of Management Studies , Vol. XI, No. Nº1 (2004): pp. 3-21.

Calzolari, Giorgio (1979): Stochastic simulation experiments on Model 5 of Bonn University. Published in: Institut fuer Gesellschafts- u. Wirtschaftswissenschaften der Universitaet Bonn No. 102 (August 1979): pp. 1-28.

Calzolari, Giorgio (1979): The deterministic simulation bias in the Klein-Goldberger model. Published in: Institut fuer Gesellschafts- u. Wirtschaftswissenschaften der Universitaet Bonn No. 100 (July 1979): pp. 1-6.

Caporin, Massimiliano and Fontini, Fulvio (2014): The value of protecting Venice from the acqua alta phenomenon under different local sea level rises.

Caporin, Massimiliano and Kolokolov, Aleksey and Renò, Roberto (2014): Multi-jumps.

Carrasco Gutierrez, Carlos Enrique and Castro Souza, Reinaldo and Teixeira de Carvalho Guillén, Osmani (2009): Selection of Optimal Lag Length in Cointegrated VAR Models with Weak Form of Common Cyclical Features. Published in: Brazilian Review of Econometrics , Vol. 29, No. 1 (2009): pp. 59-78.

Cayton, Peter Julian A. and Mapa, Dennis S. (2012): Time-varying conditional Johnson SU density in value-at-risk (VaR) methodology.

Cazotto, Gabriel (2015): Oil – The Earth’s blood, a paper on how to recover its critical declining prices by using a hedge vaccine through a leading core of countries termed as VIRUS.

Cengiz, Doruk and Tekgüç, Hasan (2022): Counterfactual Reconciliation: Incorporating Aggregation Constraints For More Accurate Causal Effect Estimates.

Cerulli, Giovanni (2020): A Super-Learning Machine for Predicting Economic Outcomes.

Chakraborty, Lekha and Chakraborty, Pinaki and Shrestha, Ruzel (2019): Budget Credibility of Subnational Governments: Analyzing the Fiscal Forecasting Errors of 28 States in India.

Chakraborty, Lekha S and Chowdhury, Samik (2005): Fiscal Marksmanship of Education Expenditure in India: Analyzing Forecast Errors through a Gender lens.

Chan, Tze-Haw and Lye, Chun Teck and Hooy, Chee-Wooi (2010): Forecasting Malaysian Exchange Rate: Do Artificial Neural Networks Work?

Chandan, Sharma and Bhanumurthy, N R (2010): Estimating Infrastructural Investment Needs for India.

Chang, Chia-Lin and Franses, Philip Hans and McAleer, Michael (2013): Are Forecast Updates Progressive?

Chatziantoniou, Ioannis and Degiannakis, Stavros and Delis, Panagiotis and Filis, George (2019): Can spillover effects provide forecasting gains? The case of oil price volatility.

Chatziantoniou, Ioannis and Degiannakis, Stavros and Eeckels, Bruno and Filis, George (2015): Forecasting Tourist Arrivals Using Origin Country Macroeconomics. Forthcoming in: Applied Economics

Chatziantoniou, Ioannis and Degiannakis, Stavros and Filis, George (2019): Futures-based forecasts: How useful are they for oil price volatility forecasting? Published in: Energy Economics No. 81 (2019): pp. 639-649.

Check, Adam J. and Nolan, Anna K. and Schipper, Tyler C. (2018): Forecasting GDP: Do Revisions Matter?

Chen, Nan-Kuang and Chen, Shiu-Sheng and Chou, Yu-Hsi (2013): Further evidence on bear market predictability: The role of the external finance premium.

Chen, Shiu-Sheng (2013): Forecasting Crude Oil Price Movements with Oil-Sensitive Stocks. Forthcoming in:

Chen, Shu-Ling and Jackson, John D. and Kim, Hyeongwoo and Resiandini, Pramesti (2012): What Drives Commodity Prices?

Chen, Song Xi and Lei, Lihua and Tu, Yundong (2014): Functional Coefficient Moving Average Model with Applications to forecasting Chinese CPI. Forthcoming in: Statistica Sinica

Chhorn, Theara and Chaiboonsri, Chukiat (2017): Modelling and Forecasting Tourist Arrivals to Cambodia: An Application of ARIMA-GARCH Approach. Published in: Journal of Management, Economics, and Industrial Organization , Vol. 2, No. 2 (2018): pp. 1-19.

Christian, Mueller-Kademann (2009): Puzzle solver.

Chu, Amanda M.Y. and Lv, Zhihui and Wagner, Niklas F. and Wong, Wing-Keung (2020): Linear and Nonlinear Growth Determinants: The Case of Mongolia and its Connection to China.

Chumacero, Romulo (2007): Altitude or hot air?

Chun, So Yeon and Shapiro, Alexander and Uryasev, Stan (2011): Conditional Value-at-Risk and Average Value-at-Risk: Estimation and Asymptotics. Forthcoming in:

Cipollini, Andrea and Missaglia, Giuseppe (2007): Dynamic Factor analysis of industry sector default rates and implication for Portfolio Credit Risk Modelling.

Cobb, Marcus P A (2017): Aggregate Density Forecasting from Disaggregate Components Using Large VARs.

Cobb, Marcus P A (2017): Forecasting Economic Aggregates Using Dynamic Component Grouping.

Cobb, Marcus P A (2018): Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach.

Cobb, Marcus P A (2017): Joint Forecast Combination of Macroeconomic Aggregates and Their Components.

Coble, David and Pincheira, Pablo (2017): Nowcasting Building Permits with Google Trends.

Cooper, Russel and Madden, Gary G (2008): Estimating components of ICT expenditure: a model-based approach with applicability to short time-series. Published in: Applied Economics , Vol. 10, No. 1 (2008)

Corradini, Riccardo (2018): A set of state space models at an high disaggregation level to forecast Italian Industrial Production.

Courtioux, Pierre (2008): How Income Contingent Loans could affect Return to Higher Education: a microsimulation of the French Case.

D'Agostino, A and Surico, P (2007): Does global liquidity help to forecast US inflation? Forthcoming in:

D'Agostino, A and Whelan, K (2007): Federal Reserve Information During the Great Moderation. Forthcoming in: Journal of the European Economic Association

D'Agostino, Antonello and McQuinn, Kieran and O'Brien, Derry (2011): Nowcasting Irish GDP.

D'Agostino, Antonello and McQuinn, Kieran and Whelan, Karl (2011): Are some forecasters really better than others?

D'Amuri, Francesco and Marcucci, Juri (2009): "Google it!" Forecasting the US unemployment rate with a Google job search index.

Dahem, Ahlem (2015): Short term Bayesian inflation forecasting for Tunisia. Published in: ECOFORUM JOURNAL , Vol. 5, No. 1 (8) (2016)

Danao, Rolando and Ducanes, Geoffrey (2016): An Error Correction Model for Forecasting Philippine Aggregate Electricity Consumption. Forthcoming in: Electricity Policy in the Philippines: Generation, Institutions, and Prices No. Stand-alone book to be published by the University of the Philippine Press (2019)

Davis, Brent (2016): “Attitudes to Leadership and Voting: Finding the Efficient Frontier”.

Davis, Brent (2017): “Negative Political Advertising: It’s All in the Timing”.

De Pooter, Michiel and Ravazzolo, Francesco and van Dijk, Dick (2006): Predicting the term structure of interest rates incorporating parameter uncertainty, model uncertainty and macroeconomic information.

Degiannakis, Stavros (2008): ARFIMAX and ARFIMAX-TARCH Realized Volatility Modeling. Published in: Journal of Applied Statistics , Vol. 10, No. 35 (2008): pp. 1169-1180.

Degiannakis, Stavros (2004): Forecasting Realized Intra-day Volatility and Value at Risk: Evidence from a Fractional Integrated Asymmetric Power ARCH Skewed-t Model. Published in: Applied Financial Economics No. 14 (2004): pp. 1333-1342.

Degiannakis, Stavros (2008): Forecasting Vix. Published in: Journal of Money, Investment and Banking No. 4 (2008): pp. 5-19.

Degiannakis, Stavros (2015): A Probit Model for the State of the Greek GDP Growth. Published in: International Journal of Financial Studies , Vol. 3, No. 3 (2015): pp. 381-392.

Degiannakis, Stavros (2021): Stock market as a nowcasting indicator for real investment.

Degiannakis, Stavros (2004): Volatility Forecasting: Evidence from a Fractional Integrated Asymmetric Power ARCH Skewed-t Model. Published in: Applied Financial Economics No. 14 (2004): pp. 1333-1342.

Degiannakis, Stavros and Dent, Pamela and Floros, Christos (2014): A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification. Published in: The Manchester School , Vol. 1, No. 82 (2014): pp. 71-102.

Degiannakis, Stavros and Filis, George (2019): Forecasting European Economic Policy Uncertainty. Published in: Scottish Journal of Political Economy , Vol. 1, No. 66 (February 2019): pp. 94-114.

Degiannakis, Stavros and Filis, George (2017): Forecasting oil price realized volatility using information channels from other asset classes. Published in: Journal of International Money and Finance No. 76 (2017): pp. 28-49.

Degiannakis, Stavros and Filis, George (2016): Forecasting oil price realized volatility: A new approach.

Degiannakis, Stavros and Filis, George (2018): Forecasting oil prices.

Degiannakis, Stavros and Filis, George (2020): Oil price assumptions for macroeconomic policy.

Degiannakis, Stavros and Filis, George (2019): Oil price volatility forecasts: What do investors need to know?

Degiannakis, Stavros and Filis, George and Hassani, Hossein (2015): Forecasting global stock market implied volatility indices. Published in: Journal of Empirical Finance No. 46 (2018): pp. 111-129.

Degiannakis, Stavros and Filis, George and Klein, Tony and Walther, Thomas (2019): Forecasting Realized Volatility of Agricultural Commodities. Forthcoming in: International Journal of Forecasting

Degiannakis, Stavros and Filis, George and Palaiodimos, George (2015): Investments and uncertainty revisited: The case of the US economy.

Degiannakis, Stavros and Floros, Christos (2013): Modeling CAC40 Volatility Using Ultra-high Frequency Data. Published in: Research in International Business and Finance No. 28 (2013): pp. 68-81.

Degiannakis, Stavros and Floros, Christos (2010): VIX Index in Interday and Intraday Volatility Models. Published in: Journal of Money, Investment and Banking No. 13 (2010): pp. 21-26.

Degiannakis, Stavros and Floros, Christos and Dent, Pamela (2013): Forecasting Value-at-Risk and Expected Shortfall using Fractionally Integrated Models of Conditional Volatility: International Evidence. Published in: International Review of Financial Analysis No. 27 (2013): pp. 21-33.

Degiannakis, Stavros and Livada, Alexandra (2016): Evaluation of Realized Volatility Predictions from Models with Leptokurtically and Asymmetrically Distributed Forecast Errors. Published in: Journal of Applied Statistics , Vol. 5, No. 43 (2016): pp. 871-892.

Degiannakis, Stavros and Livada, Alexandra (2013): Realized Volatility or Price Range: Evidence from a discrete simulation of the continuous time diffusion process. Published in: Economic Modelling No. 30 (2013): pp. 212-216.

Degiannakis, Stavros and Livada, Alexandra (2013): Realized Volatility or Price Range: Evidence from a discrete simulation of the continuous time diffusion process. Published in: Economic Modelling No. 30 (2013): pp. 212-216.

Degiannakis, Stavros and Livada, Alexandra and Panas, Epaminondas (2008): Rolling-sampled parameters of ARCH and Levy-stable models. Published in: Applied Economics , Vol. 23, No. 40 (2008): pp. 3051-3067.

Degiannakis, Stavros and Potamia, Artemis (2017): Multiple-days-ahead value-at-risk and expected shortfall forecasting for stock indices, commodities and exchange rates: inter-day versus intra-day data. Published in: International Review of Financial Analysis No. 49 (2017): pp. 176-190.

Degiannakis, Stavros and Xekalaki, Evdokia (2007): Assessing the Performance of a Prediction Error Criterion Model Selection Algorithm in the Context of ARCH Models. Published in: Applied Financial Economics No. 17 (2007): pp. 149-171.

Degiannakis, Stavros and Xekalaki, Evdokia (2005): Predictability and Model Selection in the Context of ARCH Models. Published in: Journal of Applied Stochastic Models in Business and Industry No. 21 (2005): pp. 55-82.

Degiannakis, Stavros and Xekalaki, Evdokia (2008): SPEC Model Selection Algorithm for ARCH Models: an Options Pricing Evaluation Framework. Published in: Applied Financial Economics Letters , Vol. 6, No. 4 (2008): pp. 419-423.

Degiannakis, Stavros and Xekalaki, Evdokia (2007): Simulated Evidence on the Distribution of the Standardized One-Step-Ahead Prediction Errors in ARCH Processes. Published in: Applied Financial Economics Letters No. 3 (2007): pp. 31-37.

Delavari, Majid and Gandali Alikhani, Nadiya and Naderi, Esmaeil (2012): Do Dynamic Neural Networks Stand a Better Chance in Fractionally Integrated Process Forecasting? Published in: International Journal of Economics and Financial Issues , Vol. 3, No. 2 (10 April 2013): pp. 447-465.

Delle Monache, Davide and Petrella, Ivan (2016): Adaptive models and heavy tails with an application to inflation forecasting.

Demiralay, Sercan and Ulusoy, Veysel (2014): Value-at-risk Predictions of Precious Metals with Long Memory Volatility Models.

Dicembrino, Claudio and Trovato, Giovanni (2013): Structural Breaks, Price and Income Elasticity, and Forecast of the Monthly Italian Electricity Demand.

Dimitrakopoulos, Stefanos and Tsionas, Mike G. and Aknouche, Abdelhakim (2020): Ordinal-response models for irregularly spaced transactions: A forecasting exercise.

Dimitris, Korobilis (2013): Forecasting with Factor Models: A Bayesian Model Averaging Perspective.

Dion, David Pascal (2006): Does Consumer Confidence Forecast Household Spending?

Dion, David Pascal (2006): Does Consumer Confidence Forecast Household Spending? The Euro Area Case.

Dion, David Pascal (2006): Does Consumer Confidence Forecast Household Spending? The Euro Area Case (Appendix to the main text).

Djemaci, Brahim (2016): Forecast future production of municipal waste on the basis of a panel data model in Algeria.

Djennad, Abdelmajid and Rigby, Robert and Stasinopoulos, Dimitrios and Voudouris, Vlasios and Eilers, Paul (2015): Beyond location and dispersion models: The Generalized Structural Time Series Model with Applications.

Dmitriy, Skrypnik and Marina, Shakleina (2019): Counter sanctions and well-being population of Russia: econometric analyses.

Dobrescu, Emilian (2001): Macromodel estimations for the Romanian "pre-accession economic programme. Published in: Romanian Journal of Economic Forecasting , Vol. 1, No. Supplement 1 (2002): pp. 5-38.

Dobrescu, Emilian (2001): Updated scenarios for the Romanian economy medium-term dynamics. Published in: Romanian Journal of Economic Forecasting , Vol. 1, No. 9 (2002): pp. 5-16.

Doojav, Gan-Ochir and Damdinjav, Davaasukh (2019): The policy-driven boom and bust in the housing market: Evidence from Mongolia.

Doojav, Gan-Ochir and Luvsannyam, Davaajargal (2017): Forecasting inflation in Mongolia: A dynamic model averaging approach.

Doran, Justin and Fingleton, Bernard (2012): Economic shocks and growth: spatio-temporal perspectives on Europe's economies in a time of crisis. Forthcoming in: Papers in Regional Science

Dragomirescu-Gaina, Catalin and Elia, Leandro and Weber, Anke (2014): A fast-forward look at tertiary education attainment in Europe 2020.

Ege, Yazgan and Huseyin, Kaya (2010): Has inflation targeting increased predictive power of term structure about future inflation: evidence from an emerging market ?

El Bouhadi, Abdelhamid and Achibane, Khalid (2009): The Predictive Power of Conditional Models: What Lessons to Draw with Financial Crisis in the Case of Pre-Emerging Capital Markets?

El Montasser, Ghassen and Boufateh, Talel and Issaoui, Fakhri (2013): The seasonal KPSS test when neglecting seasonal dummies: a Monte Carlo analysis.

Emara, Noha and Ma, Jinpeng (2019): An Analysis of the Seasonal Cycle and the Business Cycle.

Ermişoğlu, Ergun and Akcelik, Yasin and Oduncu, Arif (2013): GDP Growth and Credit Data.

Fagan, Stephen and Gencay, Ramazan (2008): Liquidity-Induced Dynamics in Futures Markets.

Faghih, Nezameddin and Faghih, Ali (2008): Nyquist Frequency in Sequentially Sampled Data.

Fajar, Muhammad and Hartini, Sri (2017): Inflation forecasting by hybrid singular spectrum analysis – multilayer perceptrons neural network method, case of Indonesia. Forthcoming in:

Fajar, Muhammad and Prasetyo, Octavia Rizky and Nonalisa, Septiarida and Wahyudi, Wahyudi (2020): Forecasting unemployment rate in the time of COVID-19 pandemic using Google trends data (case of Indonesia). Published in: International Journal of Scientific Research in Multidisciplinary Studies , Vol. 6, No. 11 (30 November 2020): pp. 29-33.

Falnita, Eugen and Sipos, Ciprian (2007): A multiple regression model for inflation rate in Romania in the enlarged EU. Published in: Economic integration, competition and cooperation (1 August 2007)

Fantazziini, Dean (2014): Nowcasting and Forecasting the Monthly Food Stamps Data in the US using Online Search Data. Published in: Plos One , Vol. 11, No. 9 (2014)

Fantazzini, Dean (2024): Adaptive Conformal Inference for computing Market Risk Measures: an Analysis with Four Thousands Crypto-Assets. Forthcoming in: Journal of Risk and Financial Management (2024)

Fantazzini, Dean (2023): Assessing the Credit Risk of Crypto-Assets Using Daily Range Volatility Models. Forthcoming in: Information

Fantazzini, Dean and Kurbatskii, Alexey and Mironenkov, Alexey and Lycheva, Maria (2022): Forecasting oil prices with penalized regressions, variance risk premia and Google data. Published in: Applied Econometrics

Fantazzini, Dean and Xiao, Yufeng (2023): Detecting Pump-and-Dumps with Crypto-Assets: Dealing with Imbalanced Datasets and Insiders’ Anticipated Purchases. Forthcoming in: Econometrics

Fantazzini, Dean (2022): Crypto Coins and Credit Risk: Modelling and Forecasting their Probability of Death. Forthcoming in: Journal of Risk and Financial Management

Fantazzini, Dean (2020): Discussing copulas with Sergey Aivazian: a memoir. Forthcoming in: Model Assisted Statistics and Applications : pp. 1-14.

Fantazzini, Dean (2016): The Oil Price Crash in 2014/15: Was There a (Negative) Financial Bubble? Forthcoming in: Energy Policy (2016)

Fantazzini, Dean (2020): Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries. Forthcoming in: Applied Econometrics (2020): 1 -20.

Fantazzini, Dean and Calabrese, Raffaella (2021): Crypto-exchanges and Credit Risk: Modelling and Forecasting the Probability of Closure. Published in: Journal of Risk and Financial Management , Vol. 11, No. 14 (2021)

Fantazzini, Dean and Geraskin, Petr (2011): Everything You Always Wanted to Know about Log Periodic Power Laws for Bubble Modelling but Were Afraid to Ask. Forthcoming in: European Journal of Finance

Fantazzini, Dean and Kolodin, Nikita (2020): Does the hashrate affect the bitcoin price? Forthcoming in: Journal of Risk and Financial Management (2020)

Fantazzini, Dean and Nigmatullin, Erik and Sukhanovskaya, Vera and Ivliev, Sergey (2016): Everything you always wanted to know about bitcoin modelling but were afraid to ask. Forthcoming in: Applied Econometrics (2016)

Fantazzini, Dean and Pushchelenko, Julia and Mironenkov, Alexey and Kurbatskii, Alexey (2021): Forecasting internal migration in Russia using Google Trends: Evidence from Moscow and Saint Petersburg. Published in: Forecasting , Vol. 4, No. 3 (2021): pp. 774-804.

Fantazzini, Dean and Shangina, Tamara (2019): The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades. Forthcoming in: Applied Econometrics

Fantazzini, Dean and Toktamysova, Zhamal (2015): Forecasting German Car Sales Using Google Data and Multivariate Models. Forthcoming in: International Journal of Production Economics (2015)

Fantazzini, Dean and Zimin, Stephan (2019): A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies. Forthcoming in: Journal of Industrial and Business Economics

Feng, Bo and Partridge, Mark and Rembert, Mark (2016): The Perils of Modelling How Migration Responds to Climate Change.

Feng, Dai and Yuan-Zheng, Zhong (2006): The Stochastic Advance-Retreat Course: An Approach to Analyse Social-Economic Evolution.

Ferreira Filipe, Sara and Grammatikos, Theoharry and Michala, Dimitra (2014): Forecasting Distress in European SME Portfolios.

Fildes, Robert and Madden, Gary and Tan, Joachim (2007): Optimal forecasting model selection and data characteristics. Published in: Applied Financial Economics No. 17 (2007): pp. 1251-1264.

Filippou, Miltiades and Zervopoulos, Panagiotis (2011): Developing a short-term comparative optimization forecasting model for operational units’ strategic planning.

Fingleton, Bernard (2018): Exploring Brexit with dynamic spatial panel models : some possible outcomes for employment across the EU regions.

Francesco, D'Amuri (2009): Predicting unemployment in short samples with internet job search query data.

Franco, Ray John Gabriel and Mapa, Dennis S. (2014): The Dynamics of Inflation and GDP Growth: A Mixed Frequency Model Approach.

Fries, Sébastien (2018): Conditional moments of noncausal alpha-stable processes and the prediction of bubble crash odds.

Fries, Sébastien and Zakoian, Jean-Michel (2017): Mixed Causal-Noncausal AR Processes and the Modelling of Explosive Bubbles.

Fry, J. M. (2009): Bubbles and contagion in English house prices.

Fry, J. M. (2010): Bubbles and crashes in finance: A phase transition from random to deterministic behaviour in prices.

Fry, J. M. (2010): Gaussian and non-Gaussian models for financial bubbles via econophysics.

Fry, John (2012): Exogenous and endogenous crashes as phase transitions in complex financial systems.

Fuerst, Franz (2006): Predictable or Not? Forecasting Office Markets with a Simultaneous Equation Approach.

Fullerton, Thomas M., Jr. and Kelley, Brian W. (2006): Borderplex Economic Outlook: 2006 – 2008. Published in: Business Report SR06-2 No. 2 (31 October 2006): pp. 1-23.

Fullerton, Thomas M., Jr. and Molina, Angel L., Jr. and Walke, Adam G. (2010): Tolls, Exchange Rates, and Northbound International Bridge Traffic from Mexico. Published in: Regional Science Policy & Practice , Vol. 5, No. 3 (11 July 2013): pp. 305-322.

Fullerton, Thomas M., Jr. and Mukhopadhyay, Somnath (2013): Border Region Bridge and Air Transport Predictability. Published in: Journal of Business & Economics , Vol. 4, No. 11 (11 November 2013): pp. 1089-1104.

Fullerton, Thomas M., Jr. and Ramirez, David A. and Walke, Adam G. (2013): An Econometric Analysis of Population Change in Arkansas. Published in: Oxford Journal , Vol. 9, No. 1 (11 April 2014): pp. 28-40.

Fullerton, Thomas M., Jr. and Tinajero, Roberto (2005): Borderplex Economic Outlook: 2005-2007. Published in: Business Report SR05-2 No. 2 (25 November 2005): pp. 1-21.

G.K., Chetan Kumar and K.B., Rangappa and S., Suchitra (2021): Analyzing Interlinkages between Financial and Real Estate Sector in the aftermath of COVID-19's Second wave: An Econometric Approach using VECM model. Published in: Towards Excellence , Vol. 13, No. December 2021 (1 December 2021): pp. 692-705.

G.K., Chetan Kumar and K.B., Rangappa and S., Suchitra (2022): Analyzing the Impact of Companies’ Investment on Skill Upgradation in Improving their Resilience amidst COVID-19. Published in: ATMANIRBHAR BHARAT : Opportunities and Challenges , Vol. 1, No. 1 (2022): pp. 24-37.

G.K., Chetan Kumar and K.B., Rangappa and S., Suchitra (2022): Normative analysis of the impact of Covid-19 on prominent sectors of Indian economy by using ARCH Model. Published in: Theoretical and Applied Economics , Vol. 29, No. No. 2 / 2022 (631), Summer (20 June 2022): pp. 151-164.

Gabrielsen, A. and Zagaglia, Paolo and Kirchner, A. and Liu, Z. (2012): Forecasting Value-at-Risk with time-varying variance, skewness and kurtosis in an exponential weighted moving average framework.

Galimberti, Jaqueson K. (2012): A tutorial note on the properties of ARIMA optimal forecasts.

Gan, Jumwu (2009): Burnout from pools to loans: Modeling refinancing prepayments as a self-selection process.

García, Jaume and Pérez, Levi and Rodríguez, Plácido (2016): Forecasting football match results: Are the many smarter than the few?

Garratt, Anthony and Petrella, Ivan and Zhang, Yunyi (2022): Asymmetry and Interdependence when Evaluating U.S. Energy Information Administration Forecasts.

Garratt, Anthony and Petrella, Ivan and Zhang, Yunyi (2022): Asymmetry and Interdependence when Evaluating U.S. Energy Information Agency Forecasts.

Gatt, William (2014): Communicating uncertainty - a fan chart for HICP projections. Published in: Central Bank of Malta Quarterly Review 2014:2 (September 2014): pp. 40-44.

Gelhausen, Marc Christopher (2008): Airport Choice in a Constraint World: Discrete Choice Models and Capacity Constraints. Published in: Proceedings of the Air Transport Research Society World Conference 2008 (July 2008): pp. 1-16.

Gelhausen, Marc Christopher (2006): Airport and Access Mode Choice in Germany: A Generalized Neural Logit Model Approach. Published in: Proceedings of the 2006 European Transport Conference (2006): pp. 1-32.

Gelhausen, Marc Christopher (2007): Passengers' Airport Choice. Published in: Proceedings of the Aachen Aviation Convention (AAC) 2007 (2007): pp. 41-51.

George, Michael (2007): Predicting the Profit Potential of a Microeconomic Process: An Information Theoretic/Thermodynamic Approach.

Gerlach, Richard and Naimoli, Antonio and Storti, Giuseppe (2018): Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting.

Gerlach, Richard and Naimoli, Antonio and Storti, Giuseppe (2020): Time-varying parameters Realized GARCH models for tracking attenuation bias in volatility dynamics. Forthcoming in: Quantitative Finance (2020)

Gerunov, Anton (2016): Automating Analytics: Forecasting Time Series in Economics and Business.

Ghent, Andra (2006): Comparing Models of Macroeconomic Fluctuations: How Big Are the Differences?

Ghouse, Ghulam and Khan, Saud Ahmed and Rehman, Atiq Ur (2018): ARDL model as a remedy for spurious regression: problems, performance and prospectus.

Giles, David E..A. and Tedds, Lindsay M. and Werkneh, Gugsa (2002): The Canadian Underground and Measured Economies: Granger Causality Results. Published in: Applied Economics , Vol. 18, No. 34 (2002): pp. 2347-2352.

Giovanis, Eleftherios (2008): Applications of Least Mean Square (LMS) Algorithm Regression in Time-Series Analysis.

Giovanis, Eleftherios (2008): Neuro-Fuzzy approach for the predictions of economic crisis.

Giovanis, Eleftherios (2008): Smoothing Transition Autoregressive (STAR) Models with Ordinary Least Squares and Genetic Algorithms Optimization.

Giovanis, Eleftherios (2012): Study of Discrete Choice Models and Adaptive Neuro-Fuzzy Inference System in the Prediction of Economic Crisis Periods in USA. Published in: Economic Analysis & Policy , Vol. 42, No. 1 (March 2012): pp. 79-95.

Giovanis, Eleftherios (2008): A panel data analysis for the greenhouse effects in fifteen countries of European Union.

Giovanis, eleftheios (2008): A Neuro-Fuzzy Approach in the Prediction of Financial Stability and Distress Periods.

Giovannelli, Alessandro and Proietti, Tommaso (2014): On the Selection of Common Factors for Macroeconomic Forecasting.

Glocker, Christian and Kaniovski, Serguei (2020): Structural modeling and forecasting using a cluster of dynamic factor models.

Gogas, Periklis and Pragkidis, Ioannis (2010): The interest rate spread as a forecasting tool of greek industrial production. Forthcoming in: International Journal of Business Policy and Economics

Gomez-Sorzano, Gustavo (2007): Developing the concept of Sustainable Peace using Econometrics and scenarios granting Sustainable Peace in Colombia by year 2019.

Gomez-Sorzano, Gustavo (2006): Scenarios for sustainable peace in colombia by year 2019.

Gomez-Sorzano, Gustavo (2006): The econometrics of violence, terrorism and scenarios for peace in Colombia from 1950 to 2019.

Gomez-Sorzano, Gustavo (2006): A model of cyclical terrorist murder in Colombia, 1950-2004. Forecasts 2005-2019.

Gomez-Sorzano, Gustavo (2006): A structural model for corporate profit in the U.S. industry.

Grady, Patrick (1996): Official Economic Forecasting: the Relevance of the Canadian Experience for Transitional Economies.

Grady, Patrick (1985): The state of the art in Canadian macroeconomic modelling.

Grady, Patrick and Stephenson, Donald R. (1975): Some Macroeconomic Effects of Tax Reform and Indexing. Published in: Canadian Journal of Economics , Vol. Vol. X, (August 1977): pp. 379-392.

Graefe, Andreas and Armstrong, J. Scott (2008): Forecasting Elections from Voters’ Perceptions of Candidates’ Ability to Handle Issues.

Graefe, Andreas and Armstrong, J. Scott (2012): Forecasting elections from voters’ perceptions of candidates’ ability to handle issues. Forthcoming in: Journal of Behavioral Decision Making

Graefe, Andreas and Armstrong, J. Scott and Jones, Randall J. and Cuzan, Alfred G. (2017): Assessing the 2016 U.S. Presidential Election Popular Vote Forecasts. Published in: The 2016 Presidential Election: The causes and consequences of an Electoral Earthquake (4 October 2017)

Green, Kesten C and Armstrong, J. Scott and Soon, Willie (2008): Benchmark forecasts for climate change.

Green, Kesten C and Armstrong, J. Scott and Soon, Willie (2009): Validity of Climate Change Forecasting for Public Policy Decision Making.

Green, Kesten C. and Armstrong, J. Scott (2007): Global warming: Forecasts by scientists versus scientific forecasts.

Green, Kesten C. and Armstrong, J. Scott (2009): Role thinking: Standing in other people’s shoes to forecast decisions in conflicts.

Guidi, Francesco (2008): Volatility and Long Term Relations in Equity Markets: Empirical Evidence from Germany, Switzerland, and the UK.

Guidi, Francesco and Gupta, Rakesh (2010): Cointegration and conditional correlations among German and Eastern Europe equity markets.

Guler, Bulent and Ozlale, Umit (2004): Is there a flight to quality due to inflation uncertainty? Published in: Physica A , Vol. 345, (2005): pp. 603-607.

Guo, Xu and Lam, Kin and Wong, Wing-Keung and Zhu, Lixing (2012): A New Pseudo-Bayesian Model of Investors' Behavior in Financial Crises.

Gurgul, Henryk and Lach, Łukasz (2015): Key sectors after a decade of transformation: Evidence from Poland. Published in: Managerial Economics , Vol. 16, No. 1 (1 June 2015): pp. 39-76.

Guzman, Giselle (2007): Using sentiment surveys to predict GDP growth and stock returns. Published in: The Making of National Economic Forecasts No. Edward Elgar Publishing LTD (2009): pp. 319-351.

Guzman, Giselle C. (2007): Using sentiment to predict GDP growth and stock returns. Published in: The Making of National Economic Forecasts No. Edward Elgar Publishing LTD (2009): pp. 319-351.

Guzman, Giselle C. (2010): The case for higher frequency inflation expectations.

Guzman, Giselle C. (2009): An inflation expectations horserace.

Guérin, Pierre and Leiva-Leon, Danilo (2014): Model Averaging in Markov-Switching Models: Predicting National Recessions with Regional Data.

Haider, Adnan and Hanif, Muhammad Nadeem (2007): Inflation Forecasting in Pakistan using Artificial Neural Networks.

Haider, Adnan and Safdar Ullah, Khan (2008): Estimating Output Gap for Pakistan Economy:Structural and Statistical Approaches. Published in: SBP Research Bulletin , Vol. 4, No. 1 (15 October 2008): pp. 31-60.

Halkos, George and Kevork, Ilias (2013): Forecasting the optimal order quantity in the newsvendor model under a correlated demand.

Halkos, George and Kevork, Ilias and Tziourtzioumis, Chris (2014): Emissions and abatement costs for the passenger cars sector in Greece.

Halkos, George and Kevork, Ilias and Tziourtzioumis, Chris (2014): Greenhouse gas emissions and marginal abatement cost curves for the road transport in Greece.

Harding, Don (2002): The Australian Business Cycle: A New View.

Harding, Don (2008): Detecting and forecasting business cycle turning points.

Harding, Don and Pagan, Adrian (2001): Extracting, Using and Analysing Cyclical Information.

Harin, Alexander (2009): General correcting formula of forecasting?

Harin, Alexander (2014): General correcting formulae for forecasts.

Hartmann, Daniel and Kempa, Bernd and Pierdzioch, Christian (2006): Economic and Financial Crises and the Predictability of U.S. Stock Returns.

Hartmann, Daniel and Kempa, Bernd and Pierdzioch, Christian (2006): Economic and Financial Crises and the Predictability of U.S. Stock Returns.

Hartmann, Daniel and Pierdzioch, Christian (2006): Nonlinear Links between Stock Returns and Exchange Rate Movements.

Hartmann, Daniel and Pierdzioch, Christian (2006): Nonlinear Links between Stock Returns and Exchange Rate Movements.

Hassani, Hossein (2007): Singular Spectrum Analysis: Methodology and Comparison. Published in: Journal of Data Science , Vol. 5, No. 2 (1 April 2007): pp. 239-257.

Hassett, Kevin and Zhong, Weifeng (2017): On the Observational Implications of Knightian Uncertainty.

Hasumi, Ryo and Iiboshi, Hirokuni and Matsumae, Tatsuyoshi and Nakamura, Daisuke (2018): Does a financial accelerator improve forecasts during financial crises?: Evidence from Japan with Prediction Pool Methods.

Havranek, Tomas and Zeynalov, Ayaz (2018): Forecasting Tourist Arrivals: Google Trends Meets Mixed Frequency Data.

He, Zhongfang (2009): Forecasting output growth by the yield curve: the role of structural breaks.

Hegadekatti, Kartik and S G, Yatish (2017): The Programmable Economy: Envisaging an Entire Planned Economic System as a Single Computer through Blockchain Networks. Published in: Economic Growth eJournal , Vol. 09, No. 58 (11 July 2017)

Heinen, Andreas (2003): Modelling Time Series Count Data: An Autoregressive Conditional Poisson Model.

Henzel, Steffen and Lehmann, Robert and Wohlrabe, Klaus (2015): Nowcasting Regional GDP: The Case of the Free State of Saxony.

Hernández, Juan R. (2020): Covered Interest Parity: A Stochastic Volatility Approach to Estimate the Neutral Band.

Hibbs, Douglas A. (2010): The 2010 Midterm Election for the US House of Representatives.

Hidayat, Budi (2007): Are there differences between unconditional and conditional demand estimates? implications for future research and policy. Published in: Cost Effectiveness and Resource Allocation , Vol. 6, (5 August 2008)

Horvath, Roman and Komarek, Lubos (2006): Equilibrium Exchange Rates in EU New Members: Applicable for Setting the ERM II Central Parity?

Huang, Biao (2007): Random Utility Pseudo Panel Model and Application on Car Ownership Forecast.

Huang, Biao (2007): The Use of Pseudo Panel Data for Forecasting Car Ownership.

Huseynov, Salman and Ahmadov, Vugar and Adigozalov, Shaig (2014): Beating a Random Walk: “Hard Times” for Forecasting Inflation in Post-Oil Boom Years?

Hännikäinen, Jari (2014): Multi-step forecasting in the presence of breaks.

Hännikäinen, Jari (2015): Selection of an estimation window in the presence of data revisions and recent structural breaks.

Hännikäinen, Jari (2016): When does the yield curve contain predictive power? Evidence from a data-rich environment.

Hännikäinen, Jari (2014): Zero lower bound, unconventional monetary policy and indicator properties of interest rate spreads.

Hännikäinen, Jari (2014): The mortgage spread as a predictor of real-time economic activity.

Hännikäinen, Jari (2016): The shadow rate as a predictor of real activity and inflation: Evidence from a data-rich environment.

Iiboshi, Hirokuni and Watanabe, Toshiaki (2005): Has the Business Cycle Changed in Japan? A Bayesian Analysis Based on a Markov-Switching Model with Multiple Change-Points.

Indaco, Agustín (2019): From Twitter to GDP: Estimating Economic Activity From Social Media.

Iqbal, Javed (2011): Forecasting Performance of Alternative Error Correction Models.

Iqbal, Javed (2001): Forecasting methods: a comparative analysis. Published in: Proceedings Eighth Statistics Seminar , Vol. 8, (July 2001): pp. 189-197.

Izquierdo, Segismundo S. and Hernández, Cesáreo and del Hoyo, Juan (2006): Forecasting VARMA processes using VAR models and subspace-based state space models.

Jackson, Emerson Abraham (2018): Comparison between Static and Dynamic Forecast in Autoregressive Integrated Moving Average for Seasonally Adjusted Headline Consumer Price Index.

Jackson, Emerson Abraham (2020): Understanding SLL / US$ exchange rate dynamics in Sierra Leone using Box-Jenkins ARIMA approach.

Jackson, Emerson Abraham and Tamuke, Edmund (2019): Predicting disaggregated tourist arrivals in Sierra Leone using ARIMA model. Forthcoming in: Theoretical and Practical Research in Economic Fields , Vol. 10, No. 2(20) (31 December 2019)

Jackson, Emerson Abraham and Tamuke, Edmund and Jabbie, Mohamed (2019): Disaggregated Short-Term Inflation Forecast (STIF) for Monetary Policy Decision in Sierra Leone. Published in: Financial Markets, Institutions and Risk (FMIR) , Vol. 3, No. 4 (31 November 2019): pp. 36-52.

Jadidzadeh, Ali (2022): An Application of Smooth Transition Regression Models to Homeless Research.

Jang, Tae-Seok and Sacht, Stephen (2012): Identification of Animal Spirits in a Bounded Rationality Model: An Application to the Euro Area.

Jing, Li (2009): Bootstrap prediction intervals for threshold autoregressive models.

Jing, Li and Thompson, Henry (2010): A Note on the Oil Price Trend and GARCH Shocks. Forthcoming in: Energy Journal , Vol. 31, (2010): pp. 185-191.

Josué, ANDRIANADY and M. Randriamifidy, Fitiavana and H. P. Ranaivoson, Michel and Miora Steffanie, Thierry (2023): Econometric Analysis and Forecasting of Madagascar’s Economy: An ARIMAX Approach.

Kahloul, Ines and Ben Mabrouk, Anouar and Hallara, Salah-Eddine (2009): Wavelet-Based Prediction for Governance, Diversi cation and Value Creation Variables.

Kapur, Muneesh (2018): Macroeconomic Policies and Transmission Dynamics in India.

Karamanis, Dimitrios and Kechrinioti, Alexandra (2023): The Greek-Turkish rivalry: A Bayesian VAR approach.

Karapanagiotidis, Paul (2014): Dynamic State-Space Models.

Karapanagiotidis, Paul (2012): Improving Bayesian VAR density forecasts through autoregressive Wishart Stochastic Volatility.

Karathanassis, George and Sogiakas, Vasilios (2007): Spill Over Effects of Futures Contracts Initiation on the Cash Market: A Comparative Analysis.

Kasai, Ndahiriwe and Naraidoo, Ruthira (2011): Evaluating the forecasting performance of linear and nonlinear monetary policy rules for South Africa.

Keane, Michael (1997): Current Issues in Discrete Choice Modeling. Published in: Marketing Letters , Vol. 8:3, (1997): pp. 307-322.

Keane, Michael and Moffitt, Robert (1992): THE ESTIMATION OF FOOD STAMP SELF-SELECTION MODELS USING THE METHOD OF SIMULATION.

Kenny, Geoff and Meyler, Aidan and Quinn, Terry (1998): Bayesian VAR Models for Forecasting Irish Inflation. Published in: Central Bank and Financial Services Authority of Ireland Technical Paper Series , Vol. 1998, No. 4/RT/98 (December 1998): pp. 1-37.

Khalfaoui, R and Boutahar, M (2012): Portfolio risk evaluation: An approach based on dynamic conditional correlations models and wavelet multiresolution analysis.

Khiabani, Nasser (2010): How Important are Oil and Money Shocks in Explaining Housing Market Fluctuations in an Oil-exporting Country?: Evidence from Iran.

Khudnitskaya, Alesia S. (2009): Microenvironment-specific Effects in the Application Credit Scoring Model.

Khumalo, Bhekuzulu (2009): Revisiting the Derivative: Implications on the Rate of Change Analysis.

Kim, Hyeongwoo and Durmaz, Nazif (2009): Bias Correction and Out-of-Sample Forecast Accuracy.

Kim, Hyeongwoo and Ko, Kyunghwan (2018): Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach.

Kimolo, Deogratius (2009): Modelling and Forecasting Inflation in Tanzania: A Univariate Time Series Analysis.

Kincal, Gokce and Fullerton, Thomas M., Jr. and Holcomb, James H. and Barraza de Anda, Martha P. (2010): Cross Border Business Cycle Impacts on the El Paso Housing Market. Published in: Estudios Fronterizos , Vol. 11, No. 2 (15 December 2010): pp. 49-77.

Kindop, Igor (2021): Ubiquitous multimodality in mixed causal-noncausal processes.

Kishor, N. Kundan (2009): Data Revisions in India and its Implications for Monetary Policy.

Kitov, Ivan (2007): Exact prediction of inflation and unemployment in Canada.

Kitov, Ivan (2007): Exact prediction of inflation and unemployment in Germany.

Kitov, Ivan and Kitov, Oleg and Dolinskaya, Svetlana (2007): Modelling real GDP per capita in the USA: cointegration test.

Komijani, Akbar and Naderi, Esmaeil and Gandali Alikhani, Nadiya (2013): A Hybrid Approach for Forecasting of Oil Prices Volatility.

Koop, Gary and Korobilis, Dimitris (2009): Bayesian Multivariate Time Series Methods for Empirical Macroeconomics.

Koop, Gary and Korobilis, Dimitris (2013): A New Index of Financial Conditions.

Koop, Gary and Korobilis, Dimitris (2018): Variational Bayes inference in high-dimensional time-varying parameter models.

Korobilis, Dimitris (2014): Data-based priors for vector autoregressions with drifting coefficients.

Korobilis, Dimitris (2008): Forecasting in vector autoregressions with many predictors. Published in: Advances in Econometrics , Vol. 23, (November 2008): pp. 403-431.

Korobilis, Dimitris (2011): Hierarchical shrinkage priors for dynamic regressions with many predictors.

Korobilis, Dimitris (2019): High-dimensional macroeconomic forecasting using message passing algorithms.

Korobilis, Dimitris (2009): VAR forecasting using Bayesian variable selection.

Korobilis, Dimitris and Koop, Gary (2020): Bayesian dynamic variable selection in high dimensions.

Korobilis, Dimitris and Shimizu, Kenichi (2021): Bayesian Approaches to Shrinkage and Sparse Estimation.

Kuhlmann, Stefan and Boekholt, Patries and Georghiou, Luke and Guy, Ken and Heraud, Jean-Alain and Laredo, Philippe and Lemola, Tarmo and Loveridge, Denis and Luukkonen, Terttu and Moniz, António and Polt, Wolfgang and Rip, Arie and Sanz-Menendez, Luis and Smits, Ruud (1999): Improving Distributed Intelligence in Complex Innovation Systems. Published in: ASTPP Thematic Network, TSER No. Final Report (June 1999): pp. 1-87.

Kuusela, Annika and Hännikäinen, Jari (2017): What do the shadow rates tell us about future inflation?

Kwasnicki, Witold (2011): China, India and the future of the global economy. Forthcoming in: Ekonomia, Wroclaw University of Economics

LI, XI HAO and Gallegati, Mauro (2015): Stock-Flow Dynamic Projection.

LIEBERMANN, JOELLE (2012): Real-time forecasting in a data-rich environment.

Lahiri, Kajal and Liu, Fushang (2005): ARCH models for multi-period forecast uncertainty-a reality check using a panel of density forecasts. Published in: Advances in Econometrics , Vol. 20, (2005): pp. 321-363.

Lahvicka, Jiri (2013): Impact of playoffs on seasonal uncertainty in Czech ice hockey Extraliga.

Lahvicka, Jiri (2012): Using Monte Carlo simulation to calculate match importance: the case of English Premier League.

Lai, Jennifer /J.T. (2008): Capital flow to China and the issue of hot money: an empirical investigation.

Laliotis, Ioannis (2020): The Covid-19 pandemic in Greece.

Lanne, Markku and Ahoniemi, Katja (2008): Implied Volatility with Time-Varying Regime Probabilities.

Lanne, Markku and Luoma, Arto and Luoto, Jani (2008): A Naïve Sticky Information Model of Households’ Inflation Expectations.

Lanne, Markku and Luoto, Jani (2010): Has U.S. Inflation Really Become Harder to Forecast?

Lanne, Markku and Luoto, Jani and Saikkonen, Pentti (2010): Optimal Forecasting of Noncausal Autoregressive Time Series.

Lanne, Markku and Meitz, Mika and Saikkonen, Pentti (2012): Testing for predictability in a noninvertible ARMA model.

Lanne, Markku and Nyberg, Henri and Saarinen, Erkka (2011): Forecasting U.S. Macroeconomic and Financial Time Series with Noncausal and Causal AR Models: A Comparison.

Ledenyov, Dimitri O. and Ledenyov, Viktor O. (2015): Information money fields of cyclic oscillations in nonlinear dynamic economic system.

Ledenyov, Dimitri O. and Ledenyov, Viktor O. (2015): Information money fields of cyclic oscillations in nonlinear dynamic economic system.

Ledenyov, Dimitri O. and Ledenyov, Viktor O. (2013): On the Stratonovich – Kalman - Bucy filtering algorithm application for accurate characterization of financial time series with use of state-space model by central banks.

Ledenyov, Dimitri O. and Ledenyov, Viktor O. (2014): On the winning virtuous strategies for ultra high frequency electronic trading in foreign currencies exchange markets.

Ledenyov, Dimitri O. and Ledenyov, Viktor O. (2014): On the winning virtuous strategies for ultra high frequency electronic trading in foreign currencies exchange markets.

Ledenyov, Dimitri O. and Ledenyov, Viktor O. (2015): Quantum microeconomics theory.

Ledenyov, Dimitri O. and Ledenyov, Viktor O. (2013): To the problem of evaluation of market risk of global equity index portfolio in global capital markets.

Ledenyov, Dimitri O. and Ledenyov, Viktor O. (2013): Tracking and replication of hedge fund optimal investment portfolio strategies in global capital markets in presence of nonlinearities.

Ledenyov, Dimitri O. and Ledenyov, Viktor O. (2015): Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets.

Lee, David (2023): Default Forecasting and Credit Valuation Adjustment.

Lee, Chin and Lee, Weng Hong (2008): Can financial ratios predict the Malaysian stock return? Published in: Integration & Dissemination , Vol. 2, (2008): pp. 7-8.

Lee, David (2018): Pricing Financial Derivatives Subject to Counterparty Risk and Credit Value Adjustment.

Lee, Seohyun (2017): Three essays on uncertainty: real and financial effects of uncertainty shocks.

Lehmann, Robert and Wikman, Ida (2022): Quarterly GDP Estimates for the German States.

Lehmann, Robert and Wohlrabe, Klaus (2016): Experts, firms, consumers or even hard data? Forecasting employment in Germany.

Lehmann, Robert and Wohlrabe, Klaus (2015): Looking into the Black Box of Boosting: The Case of Germany.

Lehmann, Robert and Wohlrabe, Klaus (2013): Sectoral gross value-added forecasts at the regional level: Is there any information gain?

Lehmann, Robert and Wohlrabe, Klaus (2015): The role of component-wise boosting for regional economic forecasting.

Leitao, Joao and Armada, Manuel Rocha and Ferreira, Joaaquim (2012): Corruption and Co-Movements in European Listed Sport Companies: Did Calciocaos really matter?

Lenarčič, Črt and Zorko, Robert and Herman, Uroš and Savšek, Simon (2016): A Primer on Slovene House Prices Forecast. Published in: SIR*IUS , Vol. 2017, No. 3 (2017): pp. 1-18.

Lendjoungou, Francis (2009): Competitiveness and the real exchange rate: the standpoint of countries in the CEMAC zone.

Leon, Jorge (2012): A Disaggregate Model and Second Round Effects for the CPI Inflation in Costa Rica.

Li, Chenxing and Maheu, John M (2023): Beyond Conditional Second Moments: Does Nonparametric Density Modelling Matter to Portfolio Allocation?

Li, Chenxing and Maheu, John M (2020): A Multivariate GARCH-Jump Mixture Model.

Li, Chenxing and Maheu, John M and Yang, Qiao (2022): An Infinite Hidden Markov Model with Stochastic Volatility.

Li, Kui-Wai (2011): A study on the volatility forecast of the US housing market in the 2008 crisis. Published in: Applied Financial Economics , Vol. 22, No. 22 (2012): pp. 1869-1880.

Li, Longqing (2017): A Comparative Study of GARCH and EVT Model in Modeling Value-at-Risk. Published in: Journal of Applied Business and Economics , Vol. 19, No. 7 : pp. 27-48.

Liebermann, Joelle (2010): Real-time nowcasting of GDP: Factor model versus professional forecasters.

Liew, Freddy (2012): Forecasting inflation in Asian economies. Forthcoming in:

Liew, Venus Khim-Sen and Baharumshah, Ahmad Zubaidi and Lau, Sie-Hoe (2002): Forecasting performance of Logistic STAR exchange rate model: The original and reparameterised versions. Published in: Jurnal Akademik No. December (December 2005): pp. 79-91.

Liew, Venus Khim-Sen and Shitan, Mahendran and Hussain, Huzaimi (2000): Time series modelling and forecasting of Sarawak black pepper price. Published in: Jurnal Akademik, No. June (June 2003): pp. 39-55.

Lindblad, Annika (2017): Sentiment indicators and macroeconomic data as drivers for low-frequency stock market volatility.

Liu, Jia and Maheu, John M and Song, Yong (2023): Identification and Forecasting of Bull and Bear Markets using Multivariate Returns.

Liu, Chu-An and Kuo, Biing-Shen (2016): Model Averaging in Predictive Regressions.

Liu, Xiaochun (2011): Modeling the time-varying skewness via decomposition for out-of-sample forecast.

Loermann, Julius and Maas, Benedikt (2019): Nowcasting US GDP with artificial neural networks.

Lord, Montague (1999): The Elasticities Approach to Egypt’s Balance of Payments and Equilibrium Exchange Rate.

Lord, Montague (1994): A Macroeconomic Model for Romania's Flexible Exchange Rate System.

Lord, Montague (2001): Macroeconomic Policies for Poverty Reduction in Cambodia.

Lord, Montague (2002): Modeling the Macro-Economy of Bangladesh.

Lord, Montague (1998): Modeling the Open Macro-Economy of Vietnam.

Lord, Montague (2005): Economic Growth in Uzbekistan: Sources and Potential.

Lorde, Troy and Alleyne, Antonio and Hosein, Roger and Yifei, Mu (2019): Should the Caribbean Look to the East? An Assessment of Caribbean Export Potential. Forthcoming in: The International Trade Journal

Lorde, Troy and Moore, Winston (2006): Modeling and Forecasting the Volatility of Long-stay Tourist Arrivals. Published in: Tourism Analysis , Vol. 13, No. 1 (2008): pp. 43-51.

Louzis, Dimitrios P. and Xanthopoulos-Sisinis, Spyros and Refenes, Apostolos P. (2011): Are realized volatility models good candidates for alternative Value at Risk prediction strategies?

Louzis, Dimitrios P. and Xanthopoulos-Sisinis, Spyros and Refenes, Apostolos P. (2011): The role of high frequency intra-daily data, daily range and implied volatility in multi-period Value-at-Risk forecasting.

Maas, Benedikt (2019): Nowcasting and forecasting US recessions: Evidence from the Super Learner.

Maas, Benedikt (2019): Short-term forecasting of the US unemployment rate.

MacDonald, Stephen (1992): The Accuracy of USDA's Export Forecasts. Published in: No. ERS/USDA Staff Report No. AGES 9224

MacDonald, Stephen (2005): A Comparison of USDA's Agricultural Export Forecasts with ARIMA-based Forecasts. Published in: Papers and Proceedings of the 14th Federal Forecasters Conference : pp. 155-161.

MacDonald, Stephen and Ash, Mark and Cooke, Bryce (2017): The Evolution of Inefficiency in USDA’s Forecasts of U.S. and World Soybean Markets.

Madden, Gary G and Coble-Neal, Grant (2005): Forecasting international bandwidth capability. Published in: Journal of Forecasting No. 24 (2005): pp. 299-309.

Maheu, John M and Song, Yong (2017): An Efficient Bayesian Approach to Multiple Structural Change in Multivariate Time Series.

Maheu, John M and Song, Yong and Yang, Qiao (2018): Oil Price Shocks and Economic Growth: The Volatility Link.

Maheu, John M and Yang, Qiao and Song, Yong (2018): Oil Price Shocks and Economic Growth: The Volatility Link.

Majumder, Rajarshi and Ghosh, Subhadip and Chatterjee, Bidisha (2022): Energy infrastructure in India: challenges and opportunities. Published in: Productivity , Vol. 63, No. 1 (2022): pp. 21-34.

Majumder, Rajarshi (2008): Infrastructure for Sustainable Growth: A Demand Projection Exercise for India. Published in: Journal of Quantitative Economics , Vol. 5, No. 2 (December 2007)

Malik, Afia (2018): Fuel Demand in Pakistan's TRansport Sector.

Malliaris, A.G. and Malliaris, Mary (2011): Are foreign currency markets interdependent? evidence from data mining technologies. Forthcoming in: Stochastics: Finance and Risk No. 2012

Mamatzakis, E and Christodoulakis, G (2010): A Bayesian Markov Chain Approach Using Proportions Labour Market Data for Greek Regions.

Mamatzakis, E and Remoundos, P (2010): Threshold Cointegration in BRENT crude futures market.

Mammadov, Fuad and Shaig Adigozalov, Shaiq (2014): Indicator Based Forecasting of Business Cycles in Azerbaijan.

Mandler, Martin (2008): Decomposing Federal Funds Rate forecast uncertainty using real-time data.

Mandler, Martin (2007): The Taylor rule and interest rate uncertainty in the U.S. 1970-2006.

Manzan, Sebastiano and Zerom, Dawit (2009): Are Macroeconomic Variables Useful for Forecasting the Distribution of U.S. Inflation?

Mapa, Dennis S. (2004): A Forecast Comparison of Financial Volatility Models: GARCH (1,1) is not Enough. Published in: The Philippine Statistician , Vol. 53, No. 1-4 (2004): pp. 1-10.

Mapa, Dennis S. and Cayton, Peter Julian and Lising, Mary Therese (2009): Estimating Value-at-Risk (VaR) using TiVEx-POT Models.

Mapa, Dennis S. and Lucagbo, Michael and Garcia, Heavenly Joy (2012): The Link between Agricultural Output and the States of Poverty in the Philippines: Evidence from Self-Rated Poverty Data.

Mariam, Yohannes (1999): Trends in Resource Extraction and Implications for Sustainability in Canada.

Mariam, Yohannes and Barre, Mike (1997): Statistical Time Series Analysis of Emission and Deposition of SO2 and NOx in Northeastern North America.

Matkovskyy, Roman and Bouraoui, Taoufik and Hammami, Helmi (2015): Estimation and prediction of an Index of Financial Safety of Tunisia. Published in: Research in International Business and Finance , Vol. 38, (September 2016): pp. 485-493.

McAleer, Michael and Jimenez-Martin, Juan-Angel and Perez Amaral, Teodosio (2009): Optimal Risk Management Before, During and After the 2008-09 Financial Crisis. Forthcoming in: Medium for Econometric Application , Vol. 18, No. 1 (April 2010): pp. 20-28.

McCauley, Joseph L. and Bassler, Kevin E. and Gunaratne, Gemunu H. (2007): Martingales, Detrending Data, and the Efficient Market Hypothesis.

Medel, Carlos (2015): Inflation Dynamics and the Hybrid Neo Keynesian Phillips Curve: The Case of Chile.

Medel, Carlos and Camilleri, Gilmour and Hsu, Hsiang-Ling and Kania, Stefan and Touloumtzoglou, Miltiadis (2015): Robustness in Foreign Exchange Rate Forecasting Models: Economics-based Modelling After the Financial Crisis.

Medel, Carlos and Pincheira, Pablo (2015): The Out-of-sample Performance of an Exact Median-Unbiased Estimator for the Near-Unity AR(1) Model.

Medel, Carlos A. (2015): A Critical Review of Posch, J. and F. Rumler (2015), 'Semi-Structural Forecasting of UK Inflation Based on the Hybrid New Keynesian Phillips Curve,' Journal of Forecasting 34(2): 145-62.

Medel, Carlos A. (2017): Forecasting Chilean Inflation with the Hybrid New Keynesian Phillips Curve: Globalisation, Combination, and Accuracy.

Medel, Carlos A. (2015): Forecasting Inflation with the Hybrid New Keynesian Phillips Curve: A Compact-Scale Global VAR Approach.

Medel, Carlos A. (2012): How informative are in-sample information criteria to forecasting? the case of Chilean GDP.

Medel, Carlos A. and Salgado, Sergio C. (2012): Does BIC Estimate and Forecast Better than AIC?

Mehta, Anirudh and Kanishka, Kunal (2014): Modeling and Forecasting Volatility – How Reliable are modern day approaches?

Mestiri, Sami (2021): Modelling the volatility of Bitcoin returns using Nonparametric GARCH models.

Meyler, Aidan and Kenny, Geoff and Quinn, Terry (1998): Forecasting irish inflation using ARIMA models. Published in: Central Bank and Financial Services Authority of Ireland Technical Paper Series , Vol. 1998, No. 3/RT/98 (December 1998): pp. 1-48.

Meyler, Aidan and Rubene, Ieva (2009): Results of a special questionnaire for participants in the ECB Survey of Professional Forecasters (SPF).

Mezgebo, Taddese (2012): The nature of volatility in temporal profit with in Ethiopian commodity exchange: The case of washed export coffee modelled using ARFIMA-M-HYGARCH model.

Moahmed Hassan, Hisham and Mahgoub Mohamed, Tariq (2014): Rainfall Drought Simulating Using Stochastic SARIMA Models for Gadaref Region, Sudan.

Mohajan, Devajit (2023): Mathematical Analysis of an Industry When Cost of Principal Raw Materials Increase: A Nonlinear Budget Constraint Attempt. Published in: Annals of Spiru Haret University. Economic Series , Vol. 23, No. 3 (21 October 2023): pp. 223-248.

Mohajan, Devajit (2023): Ponderal Index: An Important Anthropometric Indicator for Physical Growth. Published in: Journal of Innovations in Medical Research , Vol. 2, No. 6 (14 June 2023): pp. 15-19.

Mohajan, Devajit and Mohajan, Haradhan (2023): Economic Investigation of Lagrange Multiplier if Cost of Inputs and Budget Size of a Firm Increase: A Profit Maximization Endeavor. Published in: Annals of Spiru Haret University. Economic Series , Vol. 23, No. 2 (10 July 2023): pp. 340-364.

Mohajan, Devajit and Mohajan, Haradhan (2023): An Economical Study When Cost of Irregular Raw Materials of an Industry Increases for Nonlinear Budget Constraint. Published in: Law and Economy , Vol. 2, No. 7 (26 July 2023): pp. 24-43.

Mohajan, Devajit and Mohajan, Haradhan (2023): Effects of Various Inputs for Increased Interest Rate of Capital: A Nonlinear Budget Constraint Consideration. Published in: Frontiers in Management Science , Vol. 2, No. 4 (10 July 2023): pp. 15-33.

Mohajan, Devajit and Mohajan, Haradhan (2023): Mathematical Model for Nonlinear Budget Constraint: Economic Activities on Increased Budget. Published in: Studies in Social Science & Humanities , Vol. 5, No. 2 (11 May 2023): pp. 20-40.

Mohajan, Devajit and Mohajan, Haradhan (2023): Sensitivity Analysis of Inputs of an Organization: A Profit Maximization Exploration. Published in: Law and Economy , Vol. 2, No. 4 (15 April 2023): pp. 32-48.

Mohajan, Devajit and Mohajan, Haradhan (2023): A Study on Nonlinear Budget Constraint of a Local Industrial Firm of Bangladesh: A Profit Maximization Investigation. Published in: Law and Economy , Vol. 2, No. 5 (12 May 2023): pp. 27-33.

Mohajan, Devajit and Mohajan, Haradhan (2022): Importance of Total Coupon in Utility Maximization: A Sensitivity Analysis. Published in: Law and Economy , Vol. 1, No. 5 (6 December 2022): pp. 56-67.

Mohajan, Devajit and Mohajan, Haradhan (2022): Mathematical Analysis of SEIR Model to Prevent COVID-19 Pandemic. Published in: Journal of Economic Development, Environment and People , Vol. 11, No. 4 (31 December 2022): pp. 5-30.

Mohajan, Devajit and Mohajan, Haradhan (2022): Sensitivity Analysis between Commodity and Budget: Utility Maximization Case. Published in: Law and Economy , Vol. 2, No. 3 (24 February 2023): pp. 10-21.

Mohajan, Devajit and Mohajan, Haradhan (2023): Sensitivity Analysis between Lagrange Multipliers and Consumer Budget: Utility Maximization Case. Published in: Annals of Spiru Haret University Economic Series , Vol. 23, No. 1 (31 March 2023): pp. 167-185.

Mohajan, Devajit and Mohajan, Haradhan (2022): Sensitivity Analysis between Lagrange Multipliers and Consumer Coupon: Utility Maximization Perspective. Published in: Frontiers in Management , Vol. 2, No. 1 (17 January 2023): pp. 14-25.

Mohajan, Devajit and Mohajan, Haradhan (2023): Sensitivity Analysis for Utility Maximization: A Study on Lagrange Multipliers and Commodity Coupons. Published in: Journal of Economic Development, Environment, and People , Vol. 12, No. 1 (31 March 2023): pp. 25-40.

Mohajan, Devajit and Mohajan, Haradhan (2022): Utility Maximization Analysis of an Organization: A Mathematical Economic Procedure. Published in: Law and Economy , Vol. 3, No. 1 (26 December 2022): pp. 1-15.

Mohajan, Devajit and Mohajan, Haradhan (2022): Utility maximization analysis of an emerging firm: a bordered Hessian approach. Published in: Annals of Spiru Haret University. Economic Series , Vol. 22, No. 4 (30 December 2022): pp. 292-308.

Moniz, António (2005): Methods for Scenario-building: it’s importance for policy analysis. Published in: Proceedings of Workshop on “Innovative comparative methods for policy analysis" (September 2005): pp. 1-18.

Monokroussos, George (2015): Nowcasting in Real Time Using Popularity Priors.

Mostafavi, Moeen and Shakouri G., Hamed and Fatehi, Ali-Reza (2010): Why the determinacy condition is a weak criterion in rational expectations models. Published in: Proceeding of 2010 International Conference on Information and Finance ( ICIF 2010) (26 November 2010): pp. 208-212.

Mukherjee, Paramita and Coondoo, Dipankor and Lahiri, Poulomi (2019): Forecasting Hourly Prices in Indian Spot Electricity Market.

Mullat, Joseph (2019): The Financing Dilemma Supporting a Project.

Mustapha, Nazeem and Djolov, George (2010): The development and production of GDP flash estimates in a newly industrialised country: the case of South Africa.

Muteba Mwamba, John Weirstrass and Webb, Daniel (2014): The predictability of asset returns in the BRICS countries: a nonparametric approach.

NR, Bhanumurthy and Kumawat, Lokendra (2009): External Shocks and the Indian Economy: Analyzing through a Small, Structural Quarterly Macroeconometric Model.

NYONI, THABANI (2019): An ARIMA analysis of the Indian Rupee/USD exchange rate in India.

NYONI, THABANI (2019): ARIMA modeling and forecasting of Consumer Price Index (CPI) in Germany.

NYONI, THABANI (2019): ARIMA modeling and forecasting of inflation in Egypt (1960-2017).

NYONI, THABANI (2019): Addressing the population question in Mexico: A Box-Jenkins ARIMA approach.

NYONI, THABANI (2019): Analyzing CPI dynamics in Italy.

NYONI, THABANI (2019): Box-Jenkins ARIMA approach to predicting total population in Russia.

NYONI, THABANI (2019): A Box-Jenkins ARIMA approach to the population question in Pakistan: A reliable prognosis.

NYONI, THABANI (2019): Can Algeria be the first African country to outsmart the Malthusian population trap? Insights from the ARIMA approach.

NYONI, THABANI (2019): Demystifying inflation dynamics in Rwanda: an ARMA approach.

NYONI, THABANI (2019): Forecasting Australian CPI using ARIMA models.

NYONI, THABANI (2019): Forecasting CPI in Sweden.

NYONI, THABANI (2019): Forecasting UK consumer price index using Box-Jenkins ARIMA models.

NYONI, THABANI (2019): Forecasting consumer price index in Norway: An application of Box-Jenkins ARIMA models.

NYONI, THABANI (2019): Forecasting inflation in Burkina Faso using ARMA models.

NYONI, THABANI (2019): Forecasting the population of Brazil using the Box-Jenkins ARIMA approach.

NYONI, THABANI (2019): Forecasting total population in Yemen using Box-Jenkins ARIMA models.

NYONI, THABANI (2019): Inflation dynamics in Jamaica: Evidence from the ARMA methodology.

NYONI, THABANI (2019): Inflation dynamics in Niger unlocked: An ARMA approach.

NYONI, THABANI (2019): Is Nigeria's economy progressing or backsliding? Implications from ARIMA models.

NYONI, THABANI (2019): Is South Africa the South Africa we all desire? Insights from the Box-Jenkins ARIMA approach.

NYONI, THABANI (2019): Is the United States of America (USA) really being made great again? witty insights from the Box-Jenkins ARIMA approach.

NYONI, THABANI (2019): Modeling and forecasting CPI in Iran: A univariate analysis.

NYONI, THABANI (2019): Modeling and forecasting CPI in Mauritius.

NYONI, THABANI (2019): Modeling and forecasting CPI in Myanmar: An application of ARIMA models.

NYONI, THABANI (2019): Modeling and forecasting inflation in Burundi using ARIMA models.

NYONI, THABANI (2019): Modeling and forecasting inflation in Lesotho using Box-Jenkins ARIMA models.

NYONI, THABANI (2019): Modeling and forecasting inflation in Philippines using ARIMA models.

NYONI, THABANI (2019): Modeling and forecasting inflation in Tanzania using ARIMA models.

NYONI, THABANI (2019): Modeling and forecasting population in Bangladesh: a Box-Jenkins ARIMA approach.

NYONI, THABANI (2019): Modeling and forecasting remittances in Bangladesh using the Box-Jenkins ARIMA methodology.

NYONI, THABANI (2019): Predicting CPI in France.

NYONI, THABANI (2019): Predicting CPI in Panama.

NYONI, THABANI (2019): Predicting CPI in Singapore: An application of the Box-Jenkins methodology.

NYONI, THABANI (2019): Predicting consumer price index in Saudi Arabia.

NYONI, THABANI (2019): Predicting inflation in Senegal: An ARMA approach.

NYONI, THABANI (2019): Predicting inflation in Sri Lanka using ARMA models.

NYONI, THABANI (2019): Predicting inflation in the Kingdom of Bahrain using ARIMA models.

NYONI, THABANI (2019): Predicting total population in India: A Box-Jenkins ARIMA approach.

NYONI, THABANI (2019): Prediction of Inflation in Algeria using ARIMA models.

NYONI, THABANI (2019): Somalia population dynamics versus the Malthusian population trap: What does the ARIMA approach tell us?

NYONI, THABANI (2019): Time series modeling and forecasting of the consumer price index in Belgium.

NYONI, THABANI (2019): Time series modeling and forecasting of the consumer price index in Japan.

NYONI, THABANI (2019): Uncovering inflation dynamics in Morocco: An ARIMA approach.

NYONI, THABANI (2019): Understanding CPI dynamics in Canada.

NYONI, THABANI (2019): Understanding inflation dynamics in the United States of America (USA): A univariate approach.

NYONI, THABANI (2019): Understanding inflation patterns in Thailand: An ARMA approach.

NYONI, THABANI (2019): Understanding inflation trends in Finland: A univariate approach.

NYONI, THABANI (2019): Understanding inflation trends in Israel: A univariate approach.

NYONI, THABANI (2019): What will be Botswana's population in 2050? Evidence from the Box-Jenkins approach.

NYONI, THABANI (2019): What will be China's population in 2050? Evidence from the Box-Jenkins approach.

NYONI, THABANI (2019): Where is Eritrea going in terms of population growth? Insights from the ARIMA approach.

NYONI, THABANI (2019): Where is Kenya being headed to? Empirical evidence from the Box-Jenkins ARIMA approach.

NYONI, THABANI (2019): Will the United States of America (USA) be a beneficiary of the Alburg (1998) and Becker et al (1999) prophecies? Recent insights from the Box-Jenkins ARIMA approach.

NYONI, THABANI and MUCHINGAMI, LOVEMORE (2019): Foreign Direct Investment (FDI) dynamics in India: what do ARIMA models tell us?

NYONI, THABANI and MUCHINGAMI, LOVEMORE (2019): Modeling and forecasting Botswana's Growth Domestic Product (GDP) per capita.

NYONI, THABANI and MUTONGI, CHIPO (2019): Can Afghanistan be a victim of the Malthusian population trap? what does the ARIMA approach tell us?

NYONI, THABANI and MUTONGI, CHIPO (2019): Modeling and forecasting carbon dioxide emissions in China using Autoregressive Integrated Moving Average (ARIMA) models.

NYONI, THABANI and MUTONGI, CHIPO (2019): Modeling and forecasting inflation in The Gambia: an ARMA approach.

NYONI, THABANI and MUTONGI, CHIPO (2019): Prediction of total population in Togo using ARIMA models.

NYONI, THABANI and MUTONGI, CHIPO and MUNYARADZI, NYONI (2019): Population dynamics in Gambia: an ARIMA approach.

NYONI, THABANI and MUTONGI, CHIPO and NYONI, MUNYARADZI and HAMADZIRIPI, OSCAR HAPANYENGWI (2019): Understanding inflation dynamics in the Kingdom of Eswatini: a univariate approach.

NYONI, THABANI and NATHANIEL, SOLOMON PRINCE (2018): Modeling rates of inflation in Nigeria: an application of ARMA, ARIMA and GARCH models.

Naimoli, Antonio (2022): The information content of sentiment indices for forecasting Value at Risk and Expected Shortfall in equity markets.

Naimoli, Antonio and Storti, Giuseppe (2019): Heterogeneous component multiplicative error models for forecasting trading volumes.

Nandwa, Boaz and Mohan, Ramesh (2007): A Monetary Approach to Exchange Rate Dynamics in Low-Income Countries: Evidence from Kenya.

Naser, Hanan and Alaali, Fatema (2015): Can Oil Prices Help Predict US Stock Market Returns: An Evidence Using a DMA Approach.

Nazarian, Rafik and Gandali Alikhani, Nadiya and Naderi, Esmaeil and Amiri, Ashkan (2013): Forecasting Stock Market Volatility: A Forecast Combination Approach.

Nelimarkka, Jaakko (2017): Evidence on News Shocks under Information Deficiency.

Nguyen, Duc Khuong and Walther, Thomas (2017): Modeling and forecasting commodity market volatility with long-term economic and financial variables.

Nguyen, Phong Thanh (2020): Application Machine Learning in Construction Management. Published in: Technology, Education, Management, Informatics journal , Vol. 10, No. 03 (31 August 2021): pp. 1385-1389.

Nikolsko-Rzhevskyy, Alex (2008): Monetary Policy Evaluation in Real Time: Forward-Looking Taylor Rules Without Forward-Looking Data.

Nowotarski, Jakub and Tomczyk, Jakub and Weron, Rafal (2012): Robust estimation and forecasting of the long-term seasonal component of electricity spot prices.

Nwaobi, Godwin (2008): MODELLING THE WORLD EXCHANGE RATES:DYNAMICS, VOLATILITY AND FORECASTING.

Nyoni, Thabani (2018): Modeling and Forecasting Naira / USD Exchange Rate In Nigeria: a Box - Jenkins ARIMA approach.

Nyoni, Thabani (2019): The population question in Zimbabwe: reliable projections from the Box – Jenkins ARIMA approach.

O'Hare, Colin and Li, Youwei (2014): Identifying structural breaks in stochastic mortality models. Forthcoming in: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B. Mechanical Engineering

O'Hare, Colin and Li, Youwei (2016): Modelling mortality: Are we heading in the right direction?

O'Hare, Colin and Li, Youwei (2016): Models of Mortality rates - analysing the residuals.

Ofori, Isaac K (2021): Catching The Drivers of Inclusive Growth In Sub-Saharan Africa: An Application of Machine Learning. Forthcoming in:

Ogbonna, Ahamuefula and Olubusoye, Olusanya E (2021): Tail Risks and Stock Return Predictability: Evidence From Asia-Pacific. Published in: Asian Economic Letters , Vol. 2, No. 3 (9 July 2021)

Ojeda-Joya, Jair (2019): A consumption-based approach to exchange rate predictability.

Olalude, Gbenga Adelekan and Olayinka, Hammed Abiola and Ankeli, Uchechi Constance (2020): Modelling and forecasting inflation rate in Nigeria using ARIMA models. Published in: KASU Journal of Mathematical Sciences , Vol. 1, No. 2 (6 January 2021): pp. 127-143.

Olkhov, Victor (2023): Economic complexity limits accuracy of price probability predictions by gaussian distributions.

Olkhov, Victor (2020): Business Cycles as Collective Risk Fluctuations.

Omay, Tolga (2008): The Term Structure of Interest Rate as a Predictor of Inflation and Real Economic Activity: Nonlinear Evidence from Turkey. Forthcoming in:

Onour, Ibrahim and Sergi, Bruno (2011): Global food and energy markets: volatility transmission and impulse response effects.

Orth, Walter (2011): Multi-period credit default prediction with time-varying covariates.

Orth, Walter (2011): Multi-period credit default prediction with time-varying covariates.

Owyang, Michael T. and Piger, Jeremy and Wall, Howard J. (2012): Forecasting national recessions using state-level data.

Pang, Iris Ai Jao (2010): Comparisons of different monetary policies in China with yield curve information.

Pang, Iris Ai Jao (2010): Forecasting Hong Kong economy using factor augmented vector autoregression.

Pang, Iris Ai Jao (2010): Were Fed’s active monetary policy actions necessary?

Paunić, Alida (2007): Inflation in Croatia with outlook to future.

Pennoni, Fulvia and Bartolucci, Francesco and Forte, Gianfranco and Ametrano, Ferdinando (2020): Exploring the dependencies among main cryptocurrency log-returns: A hidden Markov model.

Perederiy, Volodymyr (2015): Endogenous derivation and forecast of lifetime PDs.

Pereira, Robert (1999): Forecasting Ability But No Profitability: An Empirical Evaluation of Genetic Algorithm-optimised Technical Trading Rules.

Photis, Yorgos N. and Koutsopoulos, Kostis (1996): Defining Demographic Change in Locational Planning Problems. Published in: Proceedings of the 36th European Regional Science Association Congress , Vol. 19, No. 19 (1996): pp. 352-373.

Photis, Yorgos N. and Manetos, Panos and Grekoussis, George (2003): Modeling urban evolution by identifying spatiotemporal patterns and applying methods of artificial intelligence.Case study: Athens, Greece. Published in: Proceedings of the 3rd Euroconference: The European City in Transition , Vol. 1, No. 1 (29 November 2003): pp. 96-108.

Piersanti, Fabio Massimo and Rizzati, Massimiliano and Nakmai, Siwat (2016): Foreign exchange rates with the Taylor rule and VECMs.

Pincheira, Pablo (2017): A Power Booster Factor for Out-of-Sample Tests of Predictability.

Pincheira, Pablo and Hardy, Nicolas (2022): Correlation Based Tests of Predictability.

Pincheira, Pablo and Hardy, Nicolas (2021): The Mean Squared Prediction Error Paradox.

Pincheira, Pablo and Hardy, Nicolas (2020): The Mean Squared Prediction Error Paradox: A summary.

Pincheira, Pablo and Hardy, Nicolas (2018): The predictive relationship between exchange rate expectations and base metal prices.

Pincheira, Pablo and Hardy, Nicolas and Bentancor, Andrea and Henriquez, Cristóbal and Tapia, Ignacio (2021): Forecasting Base Metal Prices with an International Stock Index.

Pincheira, Pablo and Hardy, Nicolás (2019): Forecasting Aluminum Prices with Commodity Currencies.

Pincheira, Pablo and Hernández, Ana María (2019): Forecasting Unemployment Rates with International Factors.

Pincheira, Pablo and Jarsun, Nabil (2020): Summary of the Paper Entitled: Forecasting Fuel Prices with the Chilean Exchange Rate.

Pincheira, Pablo and Neumann, Federico (2018): Can we beat the Random Walk? The case of survey-based exchange rate forecasts in Chile.

Poblete-Cazenave, Miguel and Pachauri, Shonali (2020): A simulation-based estimation model of household electricity demand and appliance ownership.

Poitras, Geoffrey and Heaney, John (2008): ‘How is the Stock Market Doing?’ Using Absence of Arbitrage to Measure Stock Market Performance. Published in: Annals of Financial Economcis , Vol. 4, No. 1 (15 April 2008): pp. 1-44.

Polman, Fabian M. and Krijgsman, Cees and Dajani, Karma and Hemminga, Marcus A. (2017): Modelling a Dutch Pension Fund’s Capital Requirement for Longevity Risk. Published in: Magazine De Actuaris (The Actuary) No. 24-5 (4 May 2017): pp. 38-39.

Proietti, Tommaso (2008): Direct and iterated multistep AR methods for difference stationary processes.

Proietti, Tommaso (2008): Direct and iterated multistep AR methods for difference stationary processes.

Proietti, Tommaso (2014): Exponential Smoothing, Long Memory and Volatility Prediction.

Pyzhov, Vladislav and Pyzhov, Stanislav (2017): Comparison of methods of data mining techniques for the predictive accuracy.

Pönkä, Harri (2014): Predicting the direction of US stock markets using industry returns.

Qian, Hang (2015): Inequality Constrained State Space Models.

R. Ferreira, Alexandre and A. P. Santos, Andre (2016): On the choice of covariance specifications for portfolio selection problems.

Racoceanu, Constantin (2006): Method of the exponential adjustement using directly the terms of the empiric series in the analysis of the dynamics of the textile confections production. Published in: Competitiveness and stability in the knowledge-based economy, Craiova, Romania , Vol. 2006, No. International conference (20 October 2006): pp. 266-267.

Raihan, Selim (2008): Rules of Origin and Sensitive List under SAFTA and Bilateral FTAs among South Asian Countries: Quantitative Assessments of Potential Implications for Nepal.

Raihan, Tasneem (2017): Performance of Markov-Switching GARCH Model Forecasting Inflation Uncertainty.

Ramadas, Sendhil and Palanisamy, Ramasundaram and Kuruvila, Anil and Chandrasekaran, Sundaramoorthy and Singh, Randhir and Sharma, Indu (2014): Food Price Volatility in India – Drivers, Impact and Policy Response.

Ramaharo, Franck M. and Rasolofomanana, Gerzhino H. (2023): Nowcasting Madagascar's real GDP using machine learning algorithms.

Rao, B. Bhaskara and Rao, Gyaneshwar (2007): Structural breaks and energy efficiency in Fiji.

Raputsoane, Leroi (2018): Quantifying economic recovery from the recent global financial crisis.

Rashid, Abdul and Husain, Fazal (2012): On the modeling of exchange rate: some evidence from Pakistan. Forthcoming in: International Review of Applied Financial Issues and Economics

Razzak, Weshah (2020): The Dynamic of COVID-19 New Infections under Different Stringent Policies.

Razzak, Weshah (2022): The Ownership of Oil, Democracy, and Iraq’s Past, Present, and Future.

Regnard, Nazim and Zakoian, Jean-Michel (2010): A conditionally heteroskedastic model with time-varying coefficients for daily gas spot prices.

Renfro, Charles G (2009): Building and Using a Small Macroeconometric Model: Klein Model I as an Example.

Rodríguez, Carlos A. (2004): A P* Model of Inflation in Puerto Rico. Published in: American Review of Political Economy , Vol. 2, No. 2 (September 2004): pp. 16-41.

Rosenthal, Dale W.R. (2008): Modeling trade direction. Published in: Journal of Financial Econometrics , Vol. 10, No. 2 (2012): pp. 390-415.

Rossi, Barbara and Wang, Yiru (2019): Vector autoregressive-based Granger causality test in the presence of instabilities. Published in: The Stata Journal , Vol. 19, No. 4 (December 2019): pp. 883-899.

Ruja, Catalin (2014): Macro Stress-Testing Credit Risk in Romanian Banking System.

Sabaj, Ernil and Kahveci, Mustafa (2018): Forecasting tax revenues in an emerging economy: The case of Albania.

Salisu, Afees and Salisu, Sulaiman and Salisu, Subair (2023): A news-based economic policy uncertainty index for Nigeria.

Sarmidi, Tamat (2008): Exchange Rates Predictability in Developing Countries.

Shah, Syed Sibghatullah (2019): On Trust Dynamics of Economic Growth.

Shepherd, Ben (2011): When are adaptive expectations rational? A generalization.

Silva Lopes, Artur (2024): Assessing Income Convergence with a Long-Run Forecasting Approach: Some New Results.

Sinha, Pankaj and Sharma, Aastha and Singh, Harsh Vardhan (2012): Prediction for the 2012 United States Presidential Election using Multiple Regression Model.

Sinha, Pankaj and Singhal, Anushree and Sondhi, Kriti (2012): Economic scenario of United States of America before and after 2012 U.S. Presidential Election.

Sinha, Pankaj and Thomas, Ashley Rose and Ranjan, Varun (2012): Forecasting 2012 United States Presidential election using Factor Analysis, Logit and Probit Models.

Sinha, Pankaj and Verma, Aniket and Shah, Purav and Singh, Jahnavi and Panwar, Utkarsh (2020): Prediction for the 2020 United States Presidential Election using Linear Regression Model.

Skribans, Valerijs (2003): Construction demand: a model of research and forecast for Latvia from 2002 to 2025. Published in: LU raksti (2003): pp. 90-105.

Skribans, Valerijs (2010): Construction industry forecasting system dynamic model. Published in: Proceedings of the 28th International Conference of the System Dynamics Society (2010): pp. 1-12.

Skribans, Valerijs (2011): Development of System Dynamic Model of Latvia’s Economic Integration in the EU. Published in: Proceedings of the 29th International Conference of the System Dynamics Society (2011): pp. 1-16.

Skribans, Valerijs (2010): Development of the Latvian energy sector system dynamic model. Published in: Proceedings of the 7th EUROSIM Congress on Modelling and Simulation , Vol. Vol.2:, (2010): pp. 1-8.

Skribans, Valerijs (2012): European Union Economy System Dynamic Model Development. Published in: Proceedings of the 30th International Conference of the System Dynamics Society (2012): pp. 3687-3697.

Skribans, Valerijs (2010): Investments model development with the system dynamic method. Published in: Social Research, Economics and Management: Current Issues and Perspectives , Vol. 2 (18), (2010): pp. 104-114.

Skribans, Valerijs (2010): Latvia’s incoming in European Union economic effect estimation. Published in: BUSINESS, MANAGEMENT AND EDUCATION 2010 No. Contemporary Regional Issues Conference Proceedings (2010)

Skrypnik, Dmitriy (2016): A Macroeconomic Model of the Russian Economy. Published in: "Economics and the Mathematical Methods" , Vol. 3, (September 2016)

Slavescu, Ecaterina and Panait, Iulian (2012): Improving customer churn models as one of customer relationship management business solutions for the telecommunication industry. Forthcoming in: Ovidius University Annals - Economic Sciences Series , Vol. 12, No. 1 (2012)

Soh, Ann-Ni (2020): A Review on the Leading Indicator Approach towards Economic Forecasting.

Spelta, Alessandro and Pecora, Nicolò and Flori, Andrea and Pammolli, Fabio (2018): Transition drivers and crisis signaling in stock markets.

Spiliotis, Evangelos and Petropoulos, Fotios and Kourentzes, Nikolaos and Assimakopoulos, Vassilios (2018): Cross-temporal aggregation: Improving the forecast accuracy of hierarchical electricity consumption.

Stacey, Brian (2016): A Standardized Treatment of Binary Similarity Measures with an Introduction to k-Vector Percentage Normalized Similarity.

Stephensen, Peter and Markeprand, Tobias (2013): SBAM: An algorithm for pair matching.

Su, Dongwei and He, Xingxing (2010): A Hybrid Intelligent Early Warning System for Predicting Economic Crises: The Case of China.

Sucarrat, Genaro (2020): Identification of Volatility Proxies as Expectations of Squared Financial Return.

Svetunkov, Ivan and Boylan, John Edward (2017): Multiplicative state-space models for intermittent time series.

Svetunkov, Ivan and Kourentzes, Nikolaos (2015): Complex Exponential Smoothing.

Tamayo, Adrian (2016): Determining Statistical Pattern on the Drug-Related Killing in Philippines Using ARIMA and Poisson Techniques. Forthcoming in: Journal of Drug Issues , Vol. Vol 46, No. Vol. 46, No. 4 (29 August 2016): pp. 1-13.

Teneng, Dean (2012): Modeling and forecasting foreign exchange daily closing prices with normal inverse Gaussian.

Teneng, Dean (2013): Outperforming the naïve Random Walk forecast of foreign exchange daily closing prices using Variance Gamma and normal inverse Gaussian Levy processes.

Thomadakis, Apostolos (2016): Do Combination Forecasts Outperform the Historical Average? Economic and Statistical Evidence.

Tierney, Heather L.R. (2009): Evaluating Exclusion-from-Core Measures of Inflation using Real-Time Data.

Tierney, Heather L.R. (2009): Examining the Ability of Core Inflation to Capture the Overall Trend of Total Inflation.

Tierney, Heather L.R. (2013): Forecasting and Tracking Real-Time Data Revisions in Inflation Persistence.

Tierney, Heather L.R. (2013): Forecasting and Tracking Real-Time Data Revisions in Inflation Persistence.

Tierney, Heather L.R. (2011): Forecasting and tracking real-time data revisions in inflation persistence.

Tierney, Heather L.R. (2010): Real-Time Data Revisions and the PCE Measure of Inflation.

Tierney, Heather L.R. (2010): Real-Time Data Revisions and the PCE Measure of Inflation.

Todd, Prono (2009): Simple, Skewness-Based GMM Estimation of the Semi-Strong GARCH(1,1) Model.

Todd, Prono (2009): Using skewness to estimate the semi-strong GARCH(1,1) model.

Tommaso, Proietti and Helmut, Luetkepohl (2011): Does the Box-Cox transformation help in forecasting macroeconomic time series?

Tonnerre, Antoine (2017): Merger Simulations in the American Airline Industry.

Tsyplakov, Alexander (2011): Evaluating density forecasts: a comment.

Tsyplakov, Alexander (2013): Evaluation of Probabilistic Forecasts: Proper Scoring Rules and Moments.

Tsyplakov, Alexander (2010): Revealing the arcane: an introduction to the art of stochastic volatility models.

Tsyplakov, Alexander (2014): Theoretical guidelines for a partially informed forecast examiner.

Tóth, Peter (2017): Nowcasting Slovak GDP by a Small Dynamic Factor Model. Forthcoming in: Ekonomický časopis / Journal of Economics , Vol. 65, No. 2 (2017)

UNGUREANU, Laura (2008): The Cyclicity as Evolution Form of Economic Activities.

Ubilava, David and Helmers, C Gustav (2012): Forecasting ENSO with a smooth transition autoregressive model.

Urbina, Jilber (2013): Financial Spillovers Across Countries: Measuring shock transmissions.

VINTU, Denis (2021): GDP Modelling and Forecasting Using ARIMA. An Empirical Assessment for Innovative Economy Formation. Published in: European Journal of Economic Studies , Vol. 1, No. 2021. 10 (23 April 2021): pp. 29-44.

Valerio Mendoza, Octasiano and Borsi, Mihály Tamás and Comim, Flavio (2021): Human capital dynamics in China: Evidence from a club convergence approach.

Van, Germinal (2020): Property Rights and Economic Growth in Africa: An Econometric Analysis.

Van, Germinal G. (2020): Modeling and Forecasting Economic Growth in Sub-Saharan Africa in the Post-Covid Era.

Vasios, Michalis and Payne, Richard and Nolte, Ingmar (2015): Profiting from Mimicking Strategies in Non-Anonymous Markets.

Visser, Marcel P. (2008): Forecasting S&P 500 Daily Volatility using a Proxy for Downward Price Pressure.

Voineagu, Vergil and Caragea, Nicoleta and Pisica, Silvia (2013): Estimating International Migration on the Base of Small Area Techniques.

Voisin, Elisa and Hecq, Alain (2019): Forecasting bubbles with mixed causal-noncausal autoregressive models.

Vîntu, Denis (2020): Relegating - The GDP Structural Modelling Strategy, The Dynamics in Time-Series Data: Short-Run Shocks, Disequilibrium Shocks and Innovative Shocks to Nuisance. Published in: International Scientific Conference "Economic and Social Implications of the COVID-19 Pandemic: Analysis, Forecasts and Consequences Mitigation Strategies". , Vol. I, No. 2020 (23 October 2020): pp. 51-53.

Vîntu, Denis and Negotei, Ioana-Alina (2018): Analysis of Financial Stability: The Construction of a New Composite Financial Stability Index for Euro Area. Published in: Ovidius University Annals Economic Sciences Series , Vol. XVIII, No. 1 (July 2018): pp. 264-270.

Weber, Patrick (2012): Timing asset market peaks: the role of the liquidity risk cycle of the banking system.

Weron, Rafal (2009): Forecasting wholesale electricity prices: A review of time series models. Published in: Financial Markets: Principles of Modelling, Forecasting and Decision-Making , Vol. FindEc, (2009): pp. 71-82.

Weron, Rafal and Misiorek, Adam (2008): Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models. Forthcoming in: International Journal of Forecasting

Weron, Rafal and Misiorek, Adam (2007): Heavy tails and electricity prices: Do time series models with non-Gaussian noise forecast better than their Gaussian counterparts? Published in: Prace Naukowe Akademii Ekonomicznej we Wroclawiu , Vol. 1076, (2007): pp. 472-480.

Weron, Rafal and Misiorek, Adam (2006): Point and interval forecasting of wholesale electricity prices: Evidence from the Nord Pool market. Published in: Proceedings of the Modern Electric Power Systems MEPS'06 International Symposium, September 6-8, 2006, Wrocław, Poland (2006): pp. 34-38.

Wilken, Dieter and Berster, Peter and Gelhausen, Marc Christopher (2005): Airport Choice in Germany - New Empirical Evidence of the German Air Traveller Survey 2003. Published in: Proceedings of the 9th Air Transport Research Society World Congress (2005): pp. 1-29.

Wintenberger, Olivier and Cai, Sixiang (2011): Parametric inference and forecasting in continuously invertible volatility models.

Wohlrabe, Klaus and Bührig, Pascal (2015): Forecasting Revisions of German Industrial Production.

Wolters, Maik Hendrik (2012): Evaluating point and density forecasts of DSGE models.

Yang, Bill Huajian (2017): Forward Ordinal Probability Models for Point-in-Time Probability of Default Term Structure. Forthcoming in: Journal of Risk Model Validation (September 2017)

Yang, Bill Huajian (2019): Monotonic Estimation for Probability Distribution and Multivariate Risk Scales by Constrained Minimum Generalized Cross-Entropy. Forthcoming in: International Journal of Machine Learning and Computing

Yang, Bill Huajian (2019): Monotonic Estimation for the Survival Probability over a Risk-Rated Portfolio by Discrete-Time Hazard Rate Models. Forthcoming in: International Journal of Machine Learning and Computing

Yang, Bill Huajian (2017): Point-in-Time PD Term Structure Models with Loan Credit Quality as a Component.

Yang, Bill Huajian (2017): Smoothing Algorithms by Constrained Maximum Likelihood. Forthcoming in: Journal of Risk Model Validation (September 2017)

Yang, Bill Huajian and Wu, Biao and Cui, Kaijie and Du, Zunwei and Fei, Glenn (2019): IFRS9 Expected Credit Loss Estimation: Advanced Models for Estimating Portfolio Loss and Weighting Scenario Losses. Forthcoming in: The Journal of Risk Model Validation

Yang, Bill Huajian and Yang, Jenny and Yang, Haoji (2020): Modeling Portfolio Loss by Interval Distributions. Published in: Big Data and Information Analytics , Vol. 5, No. 1 (4 August 2020): pp. 1-13.

Yang, Zixiu and Fantazzini, Dean (2022): Using crypto assets pricing methods to build technical oscillators for short-term bitcoin trading. Forthcoming in: Information

Yeboah Asuamah, Samuel (2015): An econometric investigation of forecasting liquefied petroleum gas in Ghana.

Youssef, Jamile and Ishker, Nermeen and Fakhreddine, Nour (2021): GDP Forecast of the Biggest GCC Economies Using ARIMA.

Yılmaz, Engin (2015): Forecasting tourist arrivals to Turkey. Published in: Tourism: An International Interdisciplinary Journal , Vol. 64, No. 4 (28 December 2015): pp. 435-445.

Zafar, Raja Fawad and Qayyum, Abdul and Ghouri, Saghir Pervaiz (2015): Forecasting Inflation using Functional Time Series Analysis.

Zeng, Xiangyu and Zeng, Zhezhao (2015): Modeling and Applied Research in Sustainable Development. Forthcoming in: Ecological Economy , Vol. 12, No. 163 (2015): pp. 28-39.

Zeynalov, Ayaz (2017): Forecasting Tourist Arrivals in Prague: Google Econometrics.

Zeynalov, Ayaz (2014): Nowcasting Tourist Arrivals to Prague: Google Econometrics.

Zhu, Ke and Li, Wai Keung (2014): A new Pearson-type QMLE for conditionally heteroskedastic models.

bailek, Alexandra (2018): Economic Impact Analysis of Hospital Readmission Rate and Service Quality Using Machine Learning. Published in:

da Silva Filho, Tito Nícias Teixeira (2005): Is there too much certainty when measuring uncertainty.

de Silva, Ashton (2008): Forecasting macroeconomic variables using a structural state space model.

de Silva, Ashton J (2010): Forecasting Australian Macroeconomic variables, evaluating innovations state space approaches.

de la Fonteijne, Marcel R. (2014): Okun's Law, Dead or Alive: A Fundamental Approach.

du Jardin, Philippe (2008): Bankruptcy prediction and neural networks: The contribution of variable selection methods. Published in: Proceedings of the Second European Symposium on Time Series Prediction (Estsp 2008), Helsinki University of Technology, Porvoo, Finland, (2008): pp. 271-284.

du Jardin, Philippe (2009): Bankruptcy prediction models: How to choose the most relevant variables? Published in: Bankers, Markets & Investors No. 98 (January 2009): pp. 39-46.

du Jardin, Philippe (2012): The influence of variable selection methods on the accuracy of bankruptcy prediction models. Published in: Bankers, Markets & Investors No. 116 (January 2012): pp. 20-39.

zhang, zhichao and Xie, Li and lu, xiangyun and zhang, zhuang (2014): Determinants of financial distress in u.s. large bank holding companies.

French

Ari, Ali and Dagtekin, Rustem (2007): Les Indicateurs d'Alerte de la Crise Financière de 2000-2001 en Turquie: Un Modèle de Prévision de Crise Jumelle. Published in: Région et Développement No. 26 (2007): pp. 35-50.

Bianchi, Carlo and Brillet, Jean-Louis and Calzolari, Giorgio (1984): Analyse et mesure de l'incertitude en prevision d'un modele econometrique. Application au modele mini-DMS. Published in: Annales de l'INSEE No. 54 (1984): pp. 31-62.

Buda, Rodolphe (2008): Estimation de l'emploi régional et sectoriel salarié français : application à l'année 2006.

Buda, Rodolphe (2010): Estimations de l'emploi régional salarié français détaillé au 31.12.2007 et agrégé au 31.12.2008.

Buda, Rodolphe (1994): La modélisation macroéconomique comme processus de communication : pour une formalisation finaliste des équations de comportement.

CHIKHI, Mohamed (2011): Analyse du choc informationnel et de l’hétéroscédasticité conditionnelle dans les flux de trésorerie. Published in: Recherches Economiques et Managériales , Vol. 9, (June 2011): pp. 1-15.

Chikhi, Mohamed and Terraza, Michel (2002): Un essai de prévision non paramétrique de l'action France Télécom. Published in: Working paper LAMETA No. 07 (December 2003): pp. 1-22.

GRITLI, Mohamed Ilyes (2018): Quel avenir du dinar tunisien face à l'euro ? Prévision avec le modèle ARIMA.

Kadanga, Mayo Takémsi Norris and Togbenu, Fo-Kossi Edem (2021): Modélisation et prévision du nombre d’infections au coronavirus au Togo: une approche par un modèle ARIMA avec le logiciel R.

Ngomba Bodi, Francis Ghislain and Bikai, Landry (2019): Les prévisions conditionnelles sont-elles plus précises que les prévisions inconditionnelles dans les projections de croissance et d’inflation en zone CEMAC ?

Ngomba Bodi, Francis Ghislain and Bikai, Landry (2017): Prévisions de l’inflation et de la croissance en zone CEMAC.

German

Breiding, Torsten (2006): Die Arbeitslosenversicherung in Deutschland – Beitrag zur Bekämpfung oder Ursache von Arbeitslosigkeit.

Czinkota, Thomas (2012): Zeitpunktsignale zum aktiven Portfoliomanagement.

Gelhausen, Marc Christopher (2006): Flughafen- und Zugangsverkehrsmittelwahl in Deutschland - Ein verallgemeinerter Nested Logit-Ansatz. Published in: Proceedings of Deutscher Luft- und Raumfahrtkongress 2006 (2006): pp. 529-538.

Quaas, Georg (2019): Ferndiagnose des RWI-Konjunkturmodells.

Quaas, Georg (2006): Ganzheitliche Wirkungen von Dummyvariablen auf die Prognosegenauigkeit ökonometrischer Modelle – analysiert am Beispiel des RWI-Konjunkturmodells KM59.

Wagatha, Matthias (2007): Integration, Kointegration und die Langzeitprognose von Kreditausfallzyklen.

Greek

Halkos, George and Kevork, Ilias (2014): Διαστήματα εμπιστοσύνης για εκατοστημόρια σε στάσιμες ARMA διαδικασίες: Μία εμπειρική εφαρμογή σε περιβαλλοντικά δεδομένα.

Icelandic

Olafsdottir, Katrin (2006): Úttekt á efnahagsspám Þjóðhagsstofnunar fyrir árin 1981-2002.

Indonesian

Arikha, Dahlia (2022): Strategi Pembangunan Ekonomi Islam M. Umer Chapra.

Situngkir, Hokky (2006): Value at Risk yang memperhatikan sifat statistika distribusi return. Published in:

Italian

Bianchi, Carlo and Calzolari, Giorgio and Corsi, Paolo and Sartori, Franco and Specioso, Isidoro (1974): Aggiornamento del modello al 1974 e nuove simulazioni. Published in: Il Modellaccio , Vol. 4, No. A cura di Giorgio Fua'. Milano: Franco Angeli (1977): pp. 162-188.

Calzolari, Giorgio (1987): La varianza delle previsioni nei modelli econometrici. Published in: CLEUP Editore - Padova - Italy , Vol. 3, No. Serie didattica (November 1987): pp. 1-230.

Calzolari, Giorgio and Panattoni, Lorenzo (1988): Il problema della coerenza delle previsioni nei modelli econometrici non lineari. Published in: Atti della XXXIV Riunione Scientifica della Societa' Italiana di Statistica No. Siena: Nuova Immagine Editrice, Vol 2/1 (April 1988): pp. 271-278.

Doretti, Marco (2012): Modelli di scoring per il rischio paese.

Latvian

Bessonovs, Andrejs (2010): Faktoru modeļu agregēta un dezagregēta pieeja IKP prognožu precizitātes mērīšanā. Published in: Scientific Papers University of Latvia , Vol. Vol. 7, (2010): pp. 22-33.

Skribans, Valerijs (2009): Būvniecības nozares prognozēšanas modelis. Published in: RTU zinātniskie raksti , Vol. 18, No. 3 (2009): pp. 68-82.

Skribans, Valerijs (2010): Darbaspēka migrācijas ietekme uz darba tirgu Latvijā. Published in: LU raksti , Vol. 758, (2010): pp. 189-200.

Skribans, Valerijs (2009): Krīzes un 2009. gada nodokļu politikas izmaiņu ietekme uz Latvijas ekonomiku. Published in: LU raksti No. 743. sējums (2009): pp. 189-200.

Skribans, Valerijs (2003): Latvijas būvniecības nozares attīstības prognoze.

Skribans, Valerijs (2010): Latvijas energosektora sistēmdinamikas prognozēšanas modeļa izstrāde. Published in: RTU zinātniskie raksti , Vol. 26, No. 4 (2010): pp. 34-40.

Skribans, Valerijs (2010): Latvijas iestāšanās Eiropas Savienībā ekonomiskā efekta novērtēšana. Published in: RTU zinātniskie raksti , Vol. 20, No. 3: Ekonomika un uzņēmējdarbiba (2010): pp. 108-116.

Norwegian

Gharsallah, Sofian and Sucarrat, Genaro (2019): Hvor presise er prognosene i Nasjonalbudsjettet?

Persian

Pourghorban, Mojtaba and Mamipour, Siab (2019): Day-ahead electricity price forecasting with emphasis on its volatility in Iran (GARCH combined with ARIMA models). Published in: International Conference on Innovations in Business administration and Economics

Sarfaraz, Leyla and Afsar, Amir (2005): بررسي عوامل موثر بر قيمت طلا و ارايه مدل پيش بيني قيمت آن به كمك شبكه هاي عصبي فازي. Published in: Tarbiat Modaress Economic Reasearch Journal No. 16 (2007)

Polish

Bławat, Bogusław (2012): CRI RMI - Nowy model oceny ryzyka wystąpienia trudności finansowych firm. Forthcoming in:

Portuguese

Baptista, Ricardo F. de F. and Valls Pereira, Pedro L. (2008): Análise do Desempenho de Regras de Análise Técnica Aplicada ao Mercado Intradiário do Contrato Futuro do Índice Bovespa. Forthcoming in: Revista Brasileira de Finanças , Vol. 6, No. 2 (2008)

Boainain, Pedro G. and Valls Pereira, Pedro L. (2009): “Ombro-Cabeça-Ombro”: Testando a Lucratividade do Padrão Gráfico de Análise Técnica no Mercado de Ações Brasileiro.

Caiado, Jorge and Vieira, Aníbal and Bonito, Ana and Reis, Carlos and Fernandes, Francisco (2006): Previsão da eficácia ofensiva do futebol profissional: Um caso Português. Forthcoming in: Gestin (2006)

Caleiro, António (2014): De novo acerca da sazonalidade nos nascimentos em Portugal.

Lúcio Godeiro, Lucas (2012): Estimando o VaR (Value-at-Risk) de carteiras via modelos da família GARCH e via Simulação de Monte Carlo.

Lúcio Godeiro, Lucas (2011): Previsão para as Exportações Brasileiras de 2011 utilizando modelos estruturais.

Romanian

Dobrescu, Emilian (2001): Evoluţia macromodelului economiei româneşti de tranzitie. Published in: Oeconomica , Vol. 11, No. 4 (2002): pp. 49-84.

NUCU, Anca Elena (2011): Managementul riscului de creditare: realizari actuale, analiza critica, sugestii.

Russian

BLINOV, Sergey (2017): Использование взаимосвязи между ВВП и денежной массой для экономического прогнозирования.

Elshin, Leonid and Mikhalevich, Polina (2023): Транснациональные цепочки поставок и их роль в формировании добавленной стоимости региона (на примере Республики Татарстан). Published in: Regional Economics: Theory and Practice , Vol. 8, (8 August 2023): pp. 1458-1477.

Fokin, Nikita and Haritonova, Marina (2020): Сравнительный анализ прогнозных моделей российского ВВП в условиях наличия структурных сдвигов.

Harin, Alexander (2009): Общая корректирующая формула прогнозирования.

Maiorova, Ksenia and Fokin, Nikita (2020): Наукастинг темпов роста стоимостных объемов экспорта и импорта по товарным группам.

Olenev, H.H. and Pechenkin, R.V. and Chernecov, A.M. (2007): Параллельное программирование в MATLAB м его приложения. Published in: (15 May 2007): pp. 1-120.

Olenev, Nicholas (2008): Параллельные вычисления в идентификации динамических моделей экономики // Параллельные вычислительные технологии (ПаВТ'2008): Труды международной научной конференции (Санкт-Петербург, 28 января – 1 февраля 2008 г.). – Челябинск: Изд. ЮУрГУ, 2008. – 599 с. C.207-214. Published in: (January 2008): pp. 207-214.

Polbin, Andrey and Shumilov, Andrei (2023): Прогнозирование инфляции в России с помощью TVP-модели с байесовским сжатием параметров. Published in: Voprosy statistiki , Vol. 30, No. 4 (2023): pp. 22-32.

Polbin, Andrey and Shumilov, Andrei (2024): Прогнозирование основных российских макроэкономических показателей с помощью TVP-модели с байесовским сжатием параметров.

Polterovich, Victor and Denisova, Irina and Shakleina, Marina and Bogatova, Irina and Vartanov, Sergey and Turdyeva, Natalya and Chubarova, Tatiana (2020): Социально-экономические детерминанты болезни Паркинсона для развитых и развивающихся стран.

Rumyantsev, Mikhail I. (2007): К проблеме формализации бизнес-процессов коммерческого банка. Published in: Kultura narodov Prichernomor’ya [Culture of the peoples of Prichernomorye] No. 120 (2007): pp. 137-141.

Rumyantsev, Mikhail I. (2008): Структурно-морфологический анализ бизнес-процессов коммерческого банка. Published in: Informatsionnye tekhnologii modelirovaniya i upravleniya [Information technologies of modeling and control] No. 9 (52) (2008): pp. 997-1005.

Skribans, Valerijs (2011): Разработка модели системной динамики для энергетического сектора в Латвии. Published in: Материалы 9-ой международной конференции Государственное управление в XXI веке: Традиции и инновации , Vol. Часть, (2011): pp. 540-552.

Skribans, Valerijs (2009): Влияние Трудовой Эмиграции на Рынок Труда в Латвии. Published in: Economics and Management: Current Issues and Perspectives , Vol. 15, No. 2 (19 November 2009): pp. 250-258.

Skribans, Valerijs (2010): Модель жилищного строительства в постсоциалистических странах на примере Латвии. Published in: Экономика, оценка и управление недвижимостью и природными ресурсами: материалы Междунар. науч.-практ. конф. (2010): pp. 58-66.

Skrypnik, Dmitriy (2016): BUDGET POLICY AND ECONOMIC GROWTH IN RUSSIA. OPTIMAL BUDGET RULE.

Slovak

Tóth, Peter (2014): Malý dynamický faktorový model na krátkodobé prognózovanie slovenského HDP.

Spanish

Acevedo Rueda, Rafael Alexis (2009): Eficiencia gerencial: propuesta metodológica para su medición y evaluación en el sector eléctrico de Venezuela. Published in: Visión Gerencial , Vol. 1, No. 9 (June 2010): pp. 18-29.

Barrera-Chaupis, Carlos (2014): La relación entre los ciclos discretos en la inflación y el crecimiento: Perú 1993-2012.

Cabrera-Castellanos, Luis F. (2005): Análisis de Coyuntura de la Industria Manufacturera en México. Una Propuesta Metodológica y Aplicaciones. Published in: Revista Portal , Vol. Vol. I, No. 2 (December 2005)

Dávila-Pérez, Javier and Nuñez-Mora, Jose Antonio and Ruiz-Porras, Antonio (2007): Volatilidad del Precio de la Mezcla Mexicana de Exportación.

Estrada, Fernando (2014): Estabilidad política y tributación.

Francisco, Ramirez (2011): Modelos de Estimación de la Brecha de Producto: Aplicación al PIB de la República Dominicana.

Frank, Luis (2024): Proyección del Consumo Privado de Argentina por medio de un Modelo de Corrección de Errores.

González Laxe, Fernando and Da Rocha Alvarez, Jose Maria and Armesto Pina, José Francisco and Sanchez-Fernandez, Patricio and Lago-Peñas, Santiago (2020): Economía de Galicia tras el COVID-19: prospectiva de escenarios. Published in: Informe de Conxuntura Socioeconómica de Galicia , Vol. 2, No. I (8 May 2020): pp. 1-20.

Gutierrez-Lythgoe, Antonio (2023): Autoempleo y Machine Learning: Una aplicación para España.

Gutierrez-Lythgoe, Antonio (2023): Movilidad urbana sostenible: Predicción de demanda con Inteligencia Artificial.

Maldonado, Diego and Pazmiño, Mariela (2008): Nuevas Herramientas para la Administración del Riesgo Crediticio: El caso de una Cartera Crediticia Ecuatoriana. Published in: Cuestiones Económicas , Vol. 2, No. 2 (30 September 2008): pp. 5-75.

Medel, Carlos A. (2012): ¿Akaike o Schwarz? ¿Cuál elegir para predecir el PIB chileno?

Rendón, Stephanie (2013): Detección de caídas en mercados financieros mediante análisis multifractal (exponentes locales y puntuales de Hölder): Índice accionario IPC y tipo de cambio USD/MXN.

Sánchez Navarro, Dennis (2013): Análisis de elasticidades en el mercado automotor colombiano (2009 - 2011) mediante un modelo logit anidado.

Tinoco, Marcos (2020): Modelando la volatilidad del diferencial TED: Una evaluación de pronósticos de modelos con heterocedasticidad condicional.

Urbina, Jilber (2016): Crecimiento del crédito en Nicaragua, ¿Crecimiento natural o boom crediticio? Published in: Revista de Economía y Finanzas , Vol. III, (November 2016): pp. 91-110.

Valdivia Coria, Joab Dan and Valdivia Coria, Daney David (2019): Construcción de una Bolivia artificial: Efectos de la Política Económica desde 2006.

Turkish

Bilgili, Faik (2001): ARIMA ve VAR Modellerinin Tahmin Başarılarının Karşılaştırılması. Published in: Journal of Faculty of Economics and Administrative Sciences, Erciyes University No. 17 (2001): pp. 37-53.

Bilgili, Faik (2002): VAR, ARIMA, Üstsel Düzleme, Karma ve İlave-Faktör Yöntemlerinin Özel Tüketim Harcamalarına ait Ex Post Öngörü Başarılarının Karşılaştırılması. Published in: Dokuz Eylül University, Faculty of Economics and Administrative Sciences Journal , Vol. 17, No. 1 : pp. 185-211.

Ukrainian

Matkovskyy, Roman (2012): Прогнозування розвитку економіки України на основі баєсівських авторегресійних (BVAR) моделей з різними priors. Forthcoming in: