How Can the Error Term Be Correlated with the Explanatory Variables on the R.H.S. of a Model?
- 1 Department of Economics, Kansas State University, Manhattan, KS, USA
Abstract
Since macroeconomic research cannot be replicated, most studies may claim their conclusive research findings solely based on the statistical significance of the estimated coefficients. In this framework, we use a small simulation experiment to show that if variables affect the economy through different horizons, even though the error term is not correlated with both the explanatory variables on the right-hand side (R.H.S.) of a model and the dependent variable from a traditional view, the estimated coefficients can still be biased. The evidence provided by this paper may explain the refutation and controversy results in the modern research.
- Hamilton, J.D. (1983) Oil and the Macroeconomy Since World War II. The Journal of Political Economy, 91, 228-248. https://doi.org/10.1086/261140
- Mork, K.A. (1989) Oil and the Macroeconomy When Prices Go up and down: An Extension of Hamilton’s Results. Journal of Political Economy, 97, 740-744. https://doi.org/10.1086/261625
- Hooker, M.A. (1996) What Happened to the Oil Price-Macroeconomy Relationship? Journal of Monetary Economics, 38, 195-213.
- Kilian, L. (2009) Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market. American Economic Review, 99, 1053-1069. https://doi.org/10.1257/aer.99.3.1053
- Ioannidis, J.P. (2005) Contradicted and Initially Stronger Effects in Highly Cited Clinical Research. JAMA, 294, 218-228. https://doi.org/10.1001/jama.294.2.218
- Ioannidis, J.P.A. (2005) Why Most Published Research Findings Are False. PLoS Medicine, 2, e124. https://doi.org/10.1371/journal.pmed.0020124
- Romer, P. (2016) The Trouble with Macroeconomics. The American Economist, forthcoming.
- Enders, W. (2014) Applied Econometric Time Series. 4th Edition. John Wiley, New York.