Can consumer confidence forecast household spending? Evidence from the European Commission Business and Consumer Surveys.

• Author: Cotsomitis, John A.

1. Introduction

   The analysis of the impact of consumer attitudes on consumer spending has been an area of sustained interest in the macroeconomics literature. This interest in consumer attitudes reflects a popular belief that macroeconomic outcomes depend heavily on consumers' expectations of future economic conditions. Reinforcing this belief is the fact that consumer spending accounts for 60% to 70% of the Gross Domestic Product of highly industrialized countries such as the G-7.

   During the past few decades, a number of single-country investigations have attempted to assess the predictive power of consumer confidence in forecasting household spending. For example, in the United States, Mishkin (1978) reports that the Index of Consumer Sentiment (ICS) published by the University of Michigan possesses good explanatory power for changes in durable goods. Carroll, Fuhrer, and Wilcox (1994) also find that the Michigan ICS has good predictive capability with regard to household expenditure but that its forecasting power decreases considerably when the Index is used along with other macroeconomic variables. (1) Kwan and Cotsomitis (2004) examine the robustness of Carroll, Fuhrer, and Wilcox's (1994) findings when alternative measures of consumer confidence are used in their prediction equations. They report that use of the Michigan Index of Consumer Expectations improves on the estimation results of Carroll, Fuhrer, and Wilcox (1994). Bram and Ludvigson (1998) and Ludvigson (2004) compare the forecasting performance of the Michigan ICS and the U.S. Conference Board's Index of Consumer Confidence (ICC). Their findings indicate that the Conference Board's index provides additional information about future consumer consumption that is not captured by the Michigan index. However, Chopin and Darrat (2000), utilizing a multivariate causality framework, report that the Conference Board's ICC is an unreliable predictor of U.S. retail sales.

   As regards other studies using non-U.S. data, Acemoglu and Scott (1994) employ Granger causality and regression analyses to determine if consumer confidence, as measured by the Gallup Poll in the United Kingdom, can predict future consumption. They find that consumer confidence is a leading indicator of future consumption growth. In a subsequent study, Delorme, Kamerschen, and Voeks (2002) examine whether consumer confidence and rational expectations are the same in the United Kingdom as they are in the United States. They report that the predictive ability of the U.K consumer confidence index is greater than that of the United States. Belessiotis (1996), using French data, also reports that the consumer confidence index provides decent explanatory power for future consumer spending. In Canada, Kwan and Cotsomitis (2005) find that although consumer sentiment is a reliable predictor of consumer expenditures at the national level, results obtained using regional data are quite mixed. Fan and Wong (1998) find that, unlike the case in the United States or the United Kingdom, confidence indicators in Hong Kong have little or no explanatory power in forecasting household spending.

   The existing studies on the ability of consumer confidence to predict household spending have produced mixed results. The results vary, depending on the sample period chosen, the frequency of observations (monthly or quarterly), and the different survey methodologies employed to gauge consumer attitudes. Moreover, most of these studies confine their attention to single-country investigations. Given the diversity of results, it is important to investigate the predictive power of consumer confidence on the basis of comparable time series data for as many countries as possible.

   This paper presents a first formal attempt to study the ability of consumer confidence to forecast household spending within a multicountry framework. To this end, we use two confidence indices, namely the Consumer Confidence Indicator (CCI) and the Economic Sentiment Indicator (ESI), both of which are derived from the European Commission Business and Consumer Survey (ECBCS). An important advantage of using the ECBCS data is that both the business and consumer surveys are harmonized because identical questionnaires are used in the 15 EU countries surveyed. Also, to our knowledge, the ECBCS is the most comprehensive survey of consumer and business attitudes in use today. Because of the coverage, measurability, and representativeness of these survey data, we are able to assess the predictive performance of consumer confidence with regard to household spending on the basis of data that have a reasonable degree of comparability across countries and over time and that are available for a number of countries. Our main empirical findings indicate that: (i) household spending has a slightly higher contemporaneous correlation with the ESI than with the CCI; (ii) the in-sample incremental predictive power of these confidence indicators varies significantly in our samples when important macroeconomic variables are included in the prediction equation; and (iii) the out-of-sample forecasting ability of the confidence indicators examined is quite low.

   The remainder of this paper is structured as follows. Section 2 describes the construction of the two confidence indicators. Section 3 discusses the econometric methodology and the data used in our empirical analysis. Section 4 presents our main empirical findings. Section 5 reports our out-of-sample forecasts. Section 6 offers some concluding remarks.

2. Confidence Indicators

   The ECBCS consists of five monthly surveys: Industry, Construction, Consumers, Retail Trade, and the Service sector. Since the early 1960s, the results of these surveys have provided decision makers, researchers, and managers with relevant information for the evaluation of current and future economic conditions. The rising demand for these results both by the public and the business sectors, as well as the expanding coverage in the press, seems to confirm their importance and usefulness.

   As summarized in Table 1, the CCI for each of the surveyed countries is derived from four different attitudinal questions that form part of the European Commission's consumer survey. (2) The questions inquire about the respondents' financial position, expected changes in economic situation, unemployment level, and savings attitudes over the next 12 months. For each question, there are six answers (PP, P, E, N, NN, and NA), which range from very favorable to very unfavorable. Consumer Confidence is defined as the difference between the percentages of favorable and unfavorable replies to the four questions, where PP and NN scores receive weight 1, P and N scores receive weight 1/2, and E and NA scores receive weight 0. The score for each question is equal to (PP + 1/2 P) - (NN + 1/2 N). The CCI is the arithmetic average of the scores on the four questions.

   In 1985, the European Commission designed a broader measure of confidence, namely the ESI, in order to better reflect the public's perception of future economic activity. This confidence indicator is constructed on the basis of four different confidence indicators:

1. Industrial confidence indicator [weight 40%]

2. Consumer confidence indicator [weight 20%]

3. Construction confidence indicator [weight 20%]

4. Retail trade confidence indicator [weight 20%]

   Like the CCI, the other three confidence indicators are also calculated as the arithmetic average of the scores on the questions chosen among the full set of questions of the respective survey. (3,4) The ESI is defined as the weighted mean of the scores of the four confidence indicators (indices 1-4). Because the ESI combines the judgment and attitudes of both consumers and producers, it is generally considered to be a composite leading indicator that should be more informative than the CCI in anticipating changes in the direction of the EU economy and the economies of its member countries.

3. Econometric Methodology and Data

   To examine the forecasting ability of consumer confidence on household spending, we use the prediction equations given in Carroll, Fuhrer, and Wilcox (1994), Brain and Ludvigson (1998), and Ludvigson (2004):

   [DELTA] log([C.sub.t]) = [[alpha].sub.0] + [N.summation over (i=1)] [[beta].sub.i][S.sub.t-i] + [[epsilon].sub.t], (1)

   and

   [DELTA] log([C.sub.t]) = [[alpha].sub.0] + [N.summation over (i=1)] [[beta].sub.i][S.sub.t-i] + [gamma][Z.sub.t-1] + [[epsilon].sub.t],

   where [C.sub.t] is real total personal consumption expenditures (PCE), [S.sub.t] is proxied by either the CCI, each of the four attitudinal questions (QFPE, QESE, QUE, and QSE), or the ESI, [Z.sub.t] is a vector of control variables, and [[epsilon].sub.t] is a nonautocorrelated disturbance term. Equation 1 examines whether lagged consumer confidence by itself can forecast changes in real total PCE. (5) Equation 2 is used to test the incremental predictive power of the past values of [S.sub.t] in the presence of control variables [Z.sub.t]. In this paper, the control variables, [Z.sub.t], include four lags of the dependent variable, four lags of the growth in real labor income, four lags of the log first difference in the real stock price index, fours lags of the first difference of the short-term interest rate, four lags of unemployment rate, and four lags of the confidence indicators of Germany, France, and the United Kingdom. We anticipate that consumption growth is positively associated with past labor income growth. The stock price index and the interest rate variables are used to capture important information from financial markets. The unemployment rate serves as a proxy for labor market conditions. The four lags of the confidence...