Klein, Torsten L. (2014): Communicating quantitative information: tables vs graphs.
Preview |
PDF
MPRA_paper_60514.pdf Download (683kB) | Preview |
Abstract
In applied statistics and computational econometrics a key task for researchers is to bring the sizable but unstructured body of numeric evidence, for example from Monte Carlo simulation, in a form ready for introducing to scientific dialog. At their disposal they find established means of arrangement: narrative text, tables, graphs. Employing classical principles of communication to evaluate their suitability graphical devices seem optimal. They absorb large quantities of data, and organize content into a productive tool. Graphs confirm the advantage when put to work in a standard simulation exercise. However, theory and application contrast with the norm observed in peer-reviewed journals – by a wide margin and with considerable persistency researchers prefer tables.
Item Type: | MPRA Paper |
---|---|
Original Title: | Communicating quantitative information: tables vs graphs |
Language: | English |
Keywords: | econometric and statistical methods, Monte Carlo, bivariate probit model, exogeneity testing, modes of communication, data visualization, economics of science |
Subjects: | A - General Economics and Teaching > A1 - General Economics > A14 - Sociology of Economics C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C10 - General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C35 - Discrete Regression and Qualitative Choice Models ; Discrete Regressors ; Proportions C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection Y - Miscellaneous Categories > Y1 - Data: Tables and Charts > Y10 - Data: Tables and Charts |
Item ID: | 60514 |
Depositing User: | Torsten Klein |
Date Deposited: | 11 Dec 2014 14:38 |
Last Modified: | 26 Sep 2019 08:31 |
References: | Anscombe, Francis J., 1973, “Graphs in statistical analysis”, The American Statistician 27(1), 17–21. Arribas-Bel, Daniel, Julia Koschinsky and Pedro V. Amaral, 2011, “Improving the multi-dimensional comparison of simulation results: a spatial visualization approach”, Letters in Spatial and Resource Sciences 5(2), 55–63. Chen, Chun-houh, Wolfgang Härdle and Antony Unwin (eds.), 2008, Handbook of data visualization, Berlin: Springer. Davidson, Russell and James G. MacKinnon, 1998, “Graphical methods for investigating the size and power of hypothesis tests”, Manchester School 66(1), 1–26. Davidson, Russell and James G. MacKinnon, 1999, “Bootstrap testing in nonlinear models”, International Economic Review 40(2), 487–508. Fiorio, Carlo V., Vassilis A. Hajivassiliou, Peter C.B. Phillips, 2010, “Bimodal t-ratios: the impact of thick tails on inference”, Econometrics Journal 13(2), 271–289. Ioannidis, John and Chris Doucouliagos, 2013, “What’s to know about the credibility of empirical economics?”, Journal of Economic Surveys 27(5), 997–1004. Kiefer, Nicholas M., 1982, “Testing for dependence in multivariate probit models”, Biometrika 69(1), 161–166. Klein, Torsten L., 2014a, “The small multiple in econometrics – a redesign”, mimeo, PAS Research Unit. Klein, Torsten L., 2014b, “Communicating quantitative evidence: what determines the preference for tables over graphs?”, mimeo, PAS Research Unit. Monfardini, Chiara and Rosalba Radice, 2008, “Testing exogeneity in the bivariate probit model: a Monte Carlo study”, Oxford Bulletin of Economics and Statistics 70(2), 271–282. Sargent,Thomas J. and Christopher A. Sims, 1977, “Business cycle modelling without pretending to have too much a priori economic theory”, in “New methods in business cycle research: proceedings from a conference”, Federal Reserve Bank of Minneapolis, 45–109. Sims, Christopher A., 1982, “Policy analysis with econometric models”, Brookings Papers on Economic Activity, 1982(1), 107–152. Tufte, Edward R., 1983, The visual display of quantitative information, Cheshire CN: Graphics Press. Tufte, Edward R., 1990, Envisioning information, Cheshire CN: Graphics Press. Wooldridge, Jeffrey M., 2010, Econometric analysis of cross section and panel data, 2nd edition, Cambridge MA: MIT Press. Zamora Bonilla, Jesús, 2012, “The economics of scientific knowledge”, in Uskali Mäki (ed.), Philosophy of economics, Amsterdam: North-Holland, 823–862. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/60514 |