Do Stock Market Trading Activities Forecast Recessions?
Ujjal Chatterjee (U. of Wisconsin-Milwaukee, American University of Sharjah)
August 9, 2016
This paper re-examines the existing recession forecasting models with stock market liquidity as an additional forecasting variable. We investigate three distinct aspects of stock market trading activities, namely stock market liquidity, returns and volatility as predictors of U.S. recessions. We also conduct a horse race comparison in the recession forecasting power between various stock market liquidity measures. We show that i) lower stock market liquidity signals recessions; ii) stock market liquidity and returns forecasts recessions up to three into the future, while stock market volatility has no forecasting power; iii) stock market liquidity as computed by stock transaction costs and by stock price changes to trading volume forecast recessions better than other measures in the literature; iv) stock market liquidity-based models outperform the survey of professional forecasters’ estimates of recession probabilities, and hence the results suggest that professional forecasters may need to incorporate stock market liquidity in their forecasts. The results have potential preemptive monetary policy implications.
Determinants of Consumer Sentiment Over Business Cycles: Evidence from the U.S. Surveys of Consumers
Kajal Lahiri (State U. of NY) and Yongchen Zhao (Towson University)
July 22, 2016
We study the information content of the University of Michigan’s Index of Consumer Sentiment as well as its five components. Using household data from the Surveys of Consumers, we identify the main determinants of these indicators and document their varying role over the business cycle. Our results suggest that while at the aggregate level, macroeconomic conditions explain sentiment well, important and additional information is contained at the level of households. We compare the role of objective and subjective information in determining household level sentiment, and show that significant heterogeneity in the absorption of news from local network sources is a major feature of consumer sentiment. The differential interpretation of current macroeconomic conditions is found to be more pervasive in periods of falling sentiment that typically predates business cycle peaks, and thus helps sentiment to foreshadow recessions.
O. Emre Ergungor (Federal Reserve Bank of Cleveland)
August 23, 2016
Statistical models that estimate 12-month-ahead recession probabilities using the term spread have been around for many years. However, the reliability of the term spread as a predictor may have been affected by short-term interest rates being at zero. At the zero lower bound, long-term yields cannot go too far into negative territory due to the portfolio constraints of institutional investors. Therefore, the yield curve may not invert when it should or as much as it should despite the anticipated path of the economy. I enhance the simple model with two variables that should have predictive power for recessions.
Did Okun’s Law Die after the Great Recession?
Giorgio Canarella (Calif. State U.) and Stephen M. Miller (University of Nevada)
August 19, 2016
This paper proposes an empirical framework to estimate Okun’s law which focuses on structural breaks and threshold nonlinearity. We use sequentially the Bai and Perron’s (1998, 2003) structural break and threshold methodology to enable regime-dependent as well as threshold-dependent changes in the unemployment rate. We employ an autoregressive distributed lag version of Okun’s law in first differences, which allows for delayed reactions of the unemployment rate to output changes. Applied to US data (1948Q1-2015Q4), the empirical analysis characterize Okun’s law as a three-regime relationship with the first break coinciding with the 1973 oil shock, and the second break immediately following the end of the Great Recession. In the post-Great Recession regime, we find that Okun’s law breaks down as a linear relationship. This result assumes a linear and symmetric relationship between changes in the unemployment rate and real output. We test this assumption for each of the identified regimes using threshold estimation and recognize a threshold within each regime, which rejects the linearity and symmetry hypotheses and, thus, suggests that Okun’s law follows a more complex nonlinear asymmetric dynamics. Importantly, when we apply threshold estimation to the post-Great Recession regime, we find that the time-honored link between output growth and the unemployment rate still holds.
Policy Uncertainty and the Economy
Kevin A. Hassett and Joseph W. Sullivan (American Enterprise Institute)
August 1, 2016
This paper assesses the economics literature on policy uncertainty, addresses puzzles in that literature, and highlights pertinent empirical regularities. Although much progress has been made in identifying important correlations between uncertainty and economic activity, concerns about causal identification remain. However, new empirical measures of uncertainty allow economists to ask questions with a precision likely to advance enduring debates on sources of uncertainty and their effects. The implications of elevated political polarization offer the most parsimonious explanation of what are otherwise puzzling results on the economic effects of uncertainty. According to historical data, in the month of a United States presidential election, the odds of the U.S. entering a recession within the next 12 months are roughly twice what they are in a typical month.
Can Sticky Consumption Cause Business Cycles?
David Chandler Thomas and James McClure (Ball State University)
August 19, 2016
Sticky aggregate consumption is a demonstrable phenomenon in economies throughout the world, but to our knowledge it has not yet been incorporated into capital structure macroeconomics. Doing so suggests an explanation for business cycles. On the heels of a technological advance, sticky consumption facilitates increased savings and lower real interest rates. These lower rates lead to accelerating elongations in the capital structure. Even though such elongations facilitate more rapid economic growth, such structural changes are accompanied by increased risk and an increased likelihood of systematic entrepreneurial error. Exposure of such error causes the economy to contract.
On the Exposure of the BRIC Countries to Global Economic Shocks
Ansgar Hubertus Belke (University of Duisburg-Essen), et al.
The financial crisis led to a deep recession in many industrial countries. While large emerging countries recovered relatively quickly from the financial crisis, their performance deteriorated in the last years, despite the modest recovery in advanced economies. The higher divergence of business cycles is closely linked to the Chinese transformation. During the crisis, the Chinese fiscal stimulus prevented a decline in GDP growth not only in that country, but also in resource-rich economies. The Chinese shift to consumption-driven growth led to a decline in commodity demand, and the environment became more challenging for many emerging markets. This view is supported by Bayesian VARs specified for the BRIC (Brazil, Russia, India, and China) countries. The results reveal a strong impact of international variables on GDP growth. In contrast to the other countries, China plays a crucial role in determining global trade and oil prices. Hence, the change in the Chinese growth strategy puts additional reform pressure on countries with abundant natural resources.
Oil Prices and the Global Economy: Is it Different this Time Around?
Kamiar Mohaddes (U. of Cambridge) and M. Hashem Pesaran (U. of Southern Calif.)
July 13, 2016
The recent plunge in oil prices has brought into question the generally accepted view that lower oil prices are good for the US and the global economy. In this paper, using a quarterly multi-country econometric model, we first show that a fall in oil prices tends relatively quickly to lower interest rates and inflation in most countries, and increase global real equity prices. The effects on real output are positive, although they take longer to materialize (around 4 quarters after the shock). We then re-examine the effects of low oil prices on the US economy over different sub-periods using monthly observations on real oil prices, real equity prices and real dividends. We confirm the perverse positive relationship between oil and equity prices over the period since the 2008 financial crisis highlighted in the recent literature, but show that this relationship has been unstable when considered over the longer time period of 1946-2016. In contrast, we find a stable negative relationship between oil prices and real dividends which we argue is a better proxy for economic activity (as compared to equity prices). On the supply side, the effects of lower oil prices differ widely across the different oil producers, and could be perverse initially, as some of the major oil producers try to compensate their loss of revenues by raising production. Taking demand and supply adjustments to oil price changes as a whole, we conclude that oil markets equilibrate but rather slowly, with large episodic swings between low and high oil prices.
The G7 Business Cycle in a Globalized World
Kai Carstensen and Leonard Salzmann (University of Kiel)
June 30, 2016
Using a factor structural VAR for 14 countries out of the G20 group, we document that output innovations originating outside the G7 account for shares of 10 to almost 25 percent in the business cycle fluctuations of G7 GDP growth. Using auxiliary regressions, we additionally find that these innovations contribute noticeably, relative to G7 output innovations, to short-term fluctuations in important other national G7 variables such as employment, the current account balance, inflation, and inflation volatility, and in global macroeconomic indicators like the oil price, world stock market returns, and exchange rate volatility. The results indicate that in a globalized world spillovers from emerging markets and industrial countries other than the G7 play a relevant role for major aspects of the G7 and world business cycle.
Recession Forecasting Using Bayesian Classification
Troy Davig and Aaron Smalter Hall (Federal Reserve Bank of Kansas City)
August 3, 2016
We demonstrate the use of a Naive Bayes model as a recession forecasting tool. The approach has a close connection to Markov-switching models and logistic regression but also important differences. In contrast to Markov-switching models, Naive Bayes treats National Bureau of Economic Research business cycle turning points as data rather than hidden states to be inferred by the model. Although Naive Bayes and logistic regression are asymptotically equivalent under certain distributional assumptions, the assumptions do not hold for business cycle data. As a result, Naive Bayes has a larger asymptotic error rate, but converges to the error rate faster than logistic regression, resulting in more accurate recession forecasts with limited data. We show Naive Bayes consistently outperforms logistic regression and the Survey of Professional Forecasters for real-time recession forecasting up to 12 months in advance. These results hold under standard error measures, and also under a novel measure that varies the penalty on false signals depending on when they occur within a cycle. A false signal in the middle of an expansion, for example, is penalized more heavily than one occurring close to a turning point.