Albert, Pierre and Ghassan, Hassan B. and Huiban, Jean Pierre and Martin, Michel (1992): L'Industrie Laitière Française: Modèles d'Entreprises et Formes de Concurrence/Coordination Inter-Firmes.
Alifatussaadah, Ardiana and Primariesty, Anindya Diva and Soleh, Agus Mohamad and Andriansyah, Andriansyah (2019): Nowcasting Indonesia's GDP Growth: Are Fiscal Data Useful? Published in: Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia (16 January 2020)
Ando, Tomohiro and Bai, Jushan (2021): Large-scale generalized linear longitudinal data models with grouped patterns of unobserved heterogeneity.
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.
Bakshi, Sanjeev and Pathak, Prasanta (2009): Health at Old Ages in India: Statistical Exposition of Its Socio-Cultural and Gender Dimensions.
Ben Jebli, Mehdi (2015): The Impact of Combustible Renewables and Waste Consumption and Transport on the Environmental Degradation: The Case of Tunisia.
Berg, Tim Oliver (2015): Multivariate Forecasting with BVARs and DSGE Models.
Bonga-Bonga, Lumengo and Mabe, Queen Magadi (2016): How financially integrated are trading blocs in Africa?
Braaksma, Barteld and Zeelenberg, Kees (2015): “Re-make/Re-model”: Should big data change the modelling paradigm in official statistics? Published in: Statistical Journal of the IAOS , Vol. 31, No. 2 (2015): pp. 193-202.
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.
Byambasuren, Tsenguunjav and Gochoo, Munkh-Erdene (2015): Optimizing the Structure of Mongolian Foreign Trade and the Alternative Policy of Successful Transition.
bailek, Alexandra (2018): Economic Impact Analysis of Hospital Readmission Rate and Service Quality Using Machine Learning. Published in:
Carbajal De Nova, Carolina (2014): Synthetic data: an endogeneity simulation.
Chakraborty, Lekha S and Singh, Yadawendra (2018): Fiscal Policy, as the “Employer of Last Resort”: Impact of Direct fiscal transfer (MGNREGA) on Labour Force Participation Rates in India.
Chu, Ba (2017): Composite Quasi-Likelihood Estimation of Dynamic Panels with Group-Specific Heterogeneity and Spatially Dependent Errors.
Cordero, José Manuel and Cristobal, Victor and Santín, Daniel (2017): Causal Inference on Education Policies: A Survey of Empirical Studies Using PISA, TIMSS and PIRLS.
Cordero, José Manuel and Gil, María and Pedraja Chaparro, Francisco (2016): Exploring the effect of financial literacy courses on student achievement: a cross-country approach using PISA 2012 data.
Einian, Majid and Nili, Masoud (2016): Consumption Smoothing and Borrowing Constraints: Evidence from Household Surveys of Iran.
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 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.
Fernandez, Julian (2020): Exchange Rate Uncertainty and the Interest Rate Parity.
Gangopadhyay, Kausik and Jangir, Abhishek and Sensarma, Rudra (2015): Forecasting the price of gold: An error correction approach. Published in: IIMB Management Review , Vol. 28, No. 1 (2016): pp. 6-12.
Garanasvili, Antanina and Kazimierczak, Michal and Lazaridis, George (2018): The Use of Intellectual Property Right Bundles by Firms in Copyright Intensive Industries. Forthcoming in: Review of Economic Research on Copyright Issues (RERCI)
Genge, Ewa and Bartolucci, Francesco (2019): Are attitudes towards immigration changing in Europe? An analysis based on bidimensional latent class IRT models.
Gerunov, Anton (2014): Big Data Approaches to Modeling the Labor Market. Published in: Proceedings of the International Conference on Big Data, Knowledge and Control Systems Engineering, 2014 (2014): pp. 47-56.
Glocker, Christian and Kaniovski, Serguei (2020): Structural modeling and forecasting using a cluster of dynamic factor models.
Gomez-Ruano, Gerardo (2020): Data Science: A Primer for Economists.
Hännikäinen, Jari (2016): When does the yield curve contain predictive power? Evidence from a data-rich environment.
Indaco, Agustín (2019): From Twitter to GDP: Estimating Economic Activity From Social Media.
igescu, iulia (2020): Describing Location Shifts with One Class Support Vector Machines.
Kim, Hyeongwoo and Ko, Kyunghwan (2018): Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach.
Kollár, Aladár (2021): Betting models using AI: a review on ANN, SVM, and Markov chain.
Kombarov, Sayan (2021): Action in Economics: Mathematical Derivation of Laws of Economics from the Principle of Least Action in Physics. Published in: Proceedings of International Conference of Eurasian Economies (24 August 2021): pp. 123-129.
Korobilis, Dimitris (2019): High-dimensional macroeconomic forecasting using message passing algorithms.
Korobilis, Dimitris and Shimizu, Kenichi (2021): Bayesian Approaches to Shrinkage and Sparse Estimation.
Lenarčič, Črt and Damjanović, Milan (2015): Slovene Residential Property Prices Misalignment with Fundamentals.
Levy, Daniel and Mayer, Tamir and Raviv, Alon (2020): Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers.
Levy, Daniel and Mayer, Tamir and Raviv, Alon (2022): Economists in the 2008 Financial Crisis: Slow to See, Fast to Act. Forthcoming in: Journal of Financial Stability (Forthcoming) No. Forthcoming
Loermann, Julius and Maas, Benedikt (2019): Nowcasting US GDP with artificial neural networks.
Maas, Benedikt (2019): Nowcasting and forecasting US recessions: Evidence from the Super Learner.
Maas, Benedikt (2019): Short-term forecasting of the US unemployment rate.
Maiorova, Ksenia and Fokin, Nikita (2020): Наукастинг темпов роста стоимостных объемов экспорта и импорта по товарным группам.
Mansur, Alfan and Nizar, Muhammad Afdi (2023): Supply-leading or demand-following financial sector and economic development nexus: evidence from data-rich Indonesia.
Mitrofanova, Ekaterina S. and Artamonova, Alyona V. (2016): Studying Family Formation Trajectories’ Deinstitutionalization in Russia Using Sequence Analysis. Published in: CEUR Workshop Proceeding , Vol. 1627, No. Experimental Economics and Machine Learning (25 July 2016): pp. 34-47.
Mputu Losala Lomo, Denis-Robert (2022): Application de la Classification Ascendante Hiérarchique à la Répartition des Ressources Budgétaires dans la Ville-Province de Kinshasa.
Nikitinsky, Nikita and Shashev, Sergey and Kachurina, Polina and Bespalov, Aleksander (2016): Big Data and Machine Learning in Government Projects: Expert Evaluation Case. Published in: CEUR Workshop Proceeding , Vol. 1627, No. Experimental Economics and Machine Learning (25 July 2016)
Ofori, Isaac K (2021): Catching The Drivers of Inclusive Growth In Sub-Saharan Africa: An Application of Machine Learning. Forthcoming in:
Ogunlesi, Ayodeji (2018): Agricultural Productivity, Fiscal and Trade Policies Nexus in Sub-Saharan Africa: A Panel Structural Vector Error Correction Model Analysis.
Omoshoro-Jones, Oyeyinka Sunday and Bonga-Bonga, Lumengo (2020): Intra-regional spillovers from Nigeria and South Africa to the rest of Africa: New evidence from a FAVAR model.
Pallara, Kevin (2016): The dynamic effects of government spending: a FAVAR approach.
Pinto, Claudio (2020): Fuzzy DEA models for sports data analysis: The evaluation of the relative performances of professional (virtual) football teams.
Porras, María Sylvina and Martín-Román, Ángel L. (2022): The heterogeneity of Okun’s law: A metaregression analysis.
Rahmati, Mohammad Hossein and Tavakoli, Amirhossein and Vesal, Mohammad (2019): What do one hundred million transactions tell us about demand elasticity of gasoline?
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.
Situngkir, Hokky (2015): Indonesia embraces the Data Science. Published in: SEAMS 7th Conference, Jogjakarta, Indonesia
Tagiew, Rustam and Ignatov, Dmitry I. (2017): Behavior Mining in h-index Ranking Game. Published in: CEUR Workshop Proceeding , Vol. 1968, No. Experimental Economics and Machine Learning (28 October 2017): pp. 52-61.
Tamara, Novian and Dwi Muchisha, Nadya and Andriansyah, Andriansyah and Soleh, Agus M (2020): Nowcasting Indonesia’s GDP Growth Using Machine Learning Algorithms.
Tierney, Heather L.R. and Kim, Jiyoon (June) and Nazarov, Zafar (2018): The Effects of Temporal Aggregation on Search Engine Data.
Trabelsi, Mohamed Ali (2016): Analyse des données : Résumé de cours avec exercices d’application. Published in: Editions Universitaires Européennes No. ISBN: 978-3-639-52294-5 (2016): pp. 1-43.
Urga, Giovanni and Wang, Fa (2022): Estimation and Inference for High Dimensional Factor Model with Regime Switching.
Urga, Giovanni and Wang, Fa (2022): Estimation and inference for high dimensional factor model with regime switching.
Van, Germinal (2020): The Effect of Economic Sectors on the National Income of West African Economies from 2010 to 2019: A Multiple Regression Analysis.
Verstappen, Ksenia (2018): Economics of big data: review of best papers for January 2018.
van der Plaat, Mark (2020): Loan sales and the tyranny of distance in U.S. residential mortgage lending.
Xu, Ning and Hong, Jian and Fisher, Timothy (2016): Finite-sample and asymptotic analysis of generalization ability with an application to penalized regression.
Xu, Ning and Hong, Jian and Fisher, Timothy (2016): Model selection consistency from the perspective of generalization ability and VC theory with an application to Lasso.
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
Contact us: mpra@ub.uni-muenchen.de
This repository has been built using EPrints software.
MPRA is a RePEc service hosted by .