Knowledge that Transforms

We derive the exact expression for the weights of the Hodrick-Prescott (HP) filter in a finite sample without making any assumptions about the statistical properties of the time series. We use the results to give insights into the properties of the HP filter and to build a fast algorithm with computational improvements by a factor of up to three times in samples typical in economics.

Missing data are a common challenge facing empirical researchers. This paper presents a general GMM framework and estimator for dealing with missing values of an explanatory variable in linear regression analysis. The GMM estimator is efficient under assumptions needed for consistency of linear-imputation methods. The estimator, which also allows for a specification test of the missingness assumptions, is compared to existing linear imputation, complete data, and dummy variable methods commonly used in empirical research. The dummy variable method is generally inconsistent even when data are missing completely at random, and the dummy variable method, when consistent, can be less efficient than the complete data method.

We document that rotation group bias—the tendency for the unemployment rate to vary systematically by month in sample—in the Current Population Survey (CPS) has worsened over time. Estimated unemployment rates for earlier rotation groups have grown sharply relative to later rotation groups; both should be nationally representative samples. This bias increased discretely after the 1994 CPS redesign, and rising nonresponse rates are likely a significant contributor. Survey nonresponse increased after the redesign, mirroring the evolution of rotation group bias. Consistent with this explanation, rotation group bias for households that responded in all eight interviews remained stable over time.

Previous research found that less accommodating caseworkers are more successful in placing unemployed workers into employment. This paper explores the causal mechanisms behind this result using semi-parametric mediation analysis. Analyzing rich linked job seeker-caseworker data for Switzerland, we find that the positive employment effects of less accommodating caseworkers are not driven by a particularly effective mix of labor market programs but, rather, by other dimensions of the counseling process, possibly including threats of sanctions and pressure to accept jobs.

The importance of creativity is being increasingly recognized by economists; however, the possibility that emotional factors determine creative processes is largely ignored. Building on 1,400 letters written by three famous music composers, I obtain well-being indices that span their lifetimes. The validity of this methodology is shown by linking the indices with biographical information and through estimation of the determinants of well-being. I then exploit the data and provide quantitative evidence on the existence of a causal impact of negative emotions on outstanding creativity, an association hypothesized across several disciplines since the antiquity that has not yet been convincingly established.

An important disconnect in the news view of fluctuations is the lack of consistent evidence suggestive of significant macroeconomic effects of news shocks. Findings from estimated DSGE models that in theory allow news shocks to matter quantitatively suggest that they do not. This disconnect can be resolved once we augment a DSGE model with a financial channel that provides amplification to news shocks. Our results suggest that news shocks to the future growth prospects of the economy are significant drivers of U.S. fluctuations, explaining as much as 50% and 37% of the variance in hours worked and output, respectively, in cyclical frequencies.

Using listings data, we construct a new repeat-sales house price index that describes house values at the contract date when the price is determined rather than the closing date when the property is transferred. We showthat this difference in timing helps explain several puzzles about house prices, including their strong short-term serial correlation and their weak correlation with stock prices and macroeconomic news shocks. In addition, we showthat a variant of our index that relies exclusively on listings data for recent transactions accurately reveals trends in house prices several months before existing price indexes like Case-Shiller become available.

We present a method for consistent nonparametric estimation of a demand function with nonseparable unobserved taste heterogeneity subject to the shape restriction implied by the Slutsky inequality. We use the method to estimate gasoline demand in the United States. The results reveal differences in behavior between heavy and moderate gasoline users. They also reveal variation in the responsiveness of demand to plausible changes in prices across the income distribution. We extend our estimation method to permit endogeneity of prices. The empirical results illustrate the improvements in finite-sample performance of a nonparametric estimator from imposing shape restrictions based on economic theory.

I report evidence that an anticipated strengthening of environmental policy increased emissions. I find that the breakdown of the U.S. Senate's 2010 climate effort generated positive excess returns in coal futures markets. This response appears to be driven by an increase in coal storage. The proposed legislation aimed to reduce U.S. greenhouse gas emissions after 2013, but the legislative process itself may have increased emissions by over 12 million tons of carbon dioxide leading up to April 2010.

Can a temporary economic shock to an important local industry influence long-run city population? To answer this question I study the large temporary shock to British cities caused by the U.S. CivilWar (1861–1865), which reduced cotton supplies to Britain’s important cotton textile industry. I show that this event temporarily reduced the growth rate of cities specializing in cotton textile production, relative to other English cities, and led to a persistent change in the level of city population.