Explaining U.S. consumer behavior with news sentiment

We introduce a novel dataset with a news sentiment index that was constructed from a selection of over 300,000 newspaper articles from five of the top ten U.S. newspapers by circulation. By constructing ARMA models, we show that news and consumer sentiment, when combined with other macroeconomic variables, achieve statistically significant results to explain changes in private consumption. We make three distinct findings with respect to sentiment in consumption behavior models: first, both consumer and news sentiment add explanatory power and statistical significance to conventional consumer behavior models. Second, consumer sentiment, measured by the University of Michigan Index of Consumer Sentiment, adds more explanatory power and statistical significance than news sentiment when tested individually. Third, news sentiment is able to determine the signs of all coefficients in the model correctly, whereas consumer sentiment does not. In general, we conclude that news sentiment is a useful variable to add in consumer behavior models, especially when coupled with consumer sentiment and other macroeconomic variables. Tested individually, news sentiment is as good a proxy as personal income for explaining private consumption growth when tested individually.

[1]  M. Friedman,et al.  Theory of the Consumption Function , 1957 .

[2]  David F. Hendry,et al.  Econometrics: Alchemy or Science? : Essays in Econometric Methodology , 1992 .

[3]  Irina Rish,et al.  An empirical study of the naive Bayes classifier , 2001 .

[4]  Min Wei,et al.  Do Macro Variables, Asset Markets or Surveys Forecast Inflation Better? , 2005 .

[5]  Christopher D. Carroll,et al.  Macroeconomic Expectations of Households and Professional Forecasters , 2003 .

[6]  John Y. Campbell,et al.  Consumption, Income, and Interest Rates: Reinterpreting the Time Series Evidence , 1989, NBER Macroeconomics Annual.

[7]  L. B. Thomas.  Survey Measures of Expected U.S. Inflation , 1999 .

[8]  W. Fuller,et al.  Distribution of the Estimators for Autoregressive Time Series with a Unit Root , 1979 .

[9]  Sotiris B. Kotsiantis,et al.  Increasing the Classification Accuracy of Simple Bayesian Classifier , 2004, AIMSA.

[10]  T. Breurch,et al.  A simple test for heteroscedasticity and random coefficient variation (econometrica vol 47 , 1979 .

[11]  Mark Doms,et al.  Consumer Sentiment, the Economy, and the News Media , 2004 .

[12]  H. Theil,et al.  Economic Forecasts and Policy. , 1959 .

[13]  Gwilym M. Jenkins,et al.  Time series analysis, forecasting and control , 1971 .

[14]  C. Carroll,et al.  International Evidence on Sticky Consumption Growth , 2008, Review of Economics and Statistics.

[15]  Douglas T. Breeden,et al.  Consumption, Production, Inflation and Interest Rates: A Synthesis , 1986 .

[16]  F. Hayashi.  The Permanent Income Hypothesis: Estimation and Testing by Instrumental Variables , 1982, Journal of Political Economy.

[17]  D. P. Baron,et al.  Persistent Media Bias , 2004 .

[18]  H. White.  A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity , 1980 .

[19]  Jeffrey C. Fuhrer,et al.  Does Consumer Sentiment Forecast Household Spending? If So, Why? , 1994 .

[20]  C. Granger,et al.  Spurious regressions in econometrics , 1974 .

[21]  David D. Lewis,et al.  Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval , 1998, ECML.

[22]  D. Acemoglu,et al.  Consumer Confidence and Rational Expectations: Are Agents' Beliefs Consistent with the Theory? , 1994 .

[23]  Nir Friedman,et al.  Bayesian Network Classifiers , 1997, Machine Learning.

[24]  Leslie Godfrey,et al.  Testing for multiplicative heteroskedasticity , 1978 .

[25]  R. Hall.  Stochastic Implications of the Life Cycle-Permanent Income Hypothesis: Theory and Evidence , 1978, Journal of Political Economy.

[26]  Martin Sommer.  Habit Formation and Aggregate Consumption Dynamics , 2007 .

[27]  D. Hand,et al.  Idiot's Bayes—Not So Stupid After All? , 2001 .