We analyze sectoral labor reallocation and the reversal of urbanization in the United States during the Great Depression. The widespread movement to farms, which serves as a form of migratory insurance during the crisis, is largely toward farms with low levels of mechanization. In contrast, the mechanized agricultural sector sheds workers, many of whom reallocate into low-productivity or subsistence farming. The crisis perverts the normal process of structural change in which workers displaced by farm equipment are released into more productive occupations, suggesting that macroeconomic fluctuations are an important factor determining the labor market consequences of technological change.

Occasionally binding constraints (OBCs) like the zero lower bound (ZLB) can lead to multiple equilibria, and so to belief-driven recessions. To aid in finding policies that avoid this, we derive existence and uniqueness conditions for otherwise linear models with OBCs. Our main result gives necessary and sufficient conditions for such models to have a unique (“determinate”) perfect foresight solution returning to a given steady state, for any initial condition. While standard New Keynesian models have multiple perfect-foresight paths eventually escaping the ZLB, price level targeting restores uniqueness. We also derive equilibrium existence conditions under rational expectations for arbitrary nonlinear models.

This paper examines the impact of manufacturing employment decline on the socioeconomic outcomes within and between black and white americans since 1960. The analysis shows that manufacturing decline had a negative impact on blacks in terms of their wages, employment, marriage rates, house values, poverty rates, death rates, single parenthood, teen motherhood, child poverty, and child mortality. In addition, the decline in manufacturing increased inequality within the black community for wages and other outcomes. Similar patterns are found for whites, but to a lesser degree—leading to larger gaps between whites and blacks in wages, marriage patterns, poverty, single-parenthood, and death rates.

Here’s why. (a) The Hodrick-Prescott (HP) filter introduces spurious dynamic relations that have no basis in the underlying data-generating process. (b) Filtered values at the end of the sample are very different from those in the middle and are also characterized by spurious dynamics. (c) A statistical formalization of the problem typically produces values for the smoothing parameter vastly at odds with common practice. (d) There is a better alternative. A regression of the variable at date t on the four most recent values as of date t - h achieves all the objectives sought by users of the HP filter with none of its drawbacks.

This paper examines the relationship between the minimum high school dropout age and juvenile arrest rates by exploiting state-level variation in dropout age laws. County-level arrest data for the period 1980 to 2008 and difference-in-difference-in-difference-type empirical strategy are used to compare the arrest rates over time of various age groups within counties that differ by their state's minimum dropout age. The evidence suggests that minimum dropout age requirements have a significant and negative effect on property and violent crime arrest rates for individuals 16 to 18 years old. The results are consistent with an incapacitation effect of schooling.

This paper examines dynamic pricing behavior in Canadian retail gasoline markets. I find three distinct pricing patterns: cost-based pricing, sticky pricing, and sharp asymmetric retail price cycles that resemble the Edgeworth cycles of Maskin and Tirole (1988). I use a Markov-switching regression to estimate the prevalence of the regimes and the structural characteristics of the cycles themselves. I find cycles are more prevalent when there are more small firms and are accelerated and amplified with very many small firms. In markets with few small firms, sticky pricing dominates. The findings are consistent with the theory of Edgeworth cycles.

Estimates of the Taylor rule using historical data from the past decade or two suggest that monetary policy in the U.S. can be characterized as having reacted in a moderate fashion to output and inflation gaps. In contrast, the parameters of optimal Taylor rules derived using empirical models of the economy often recommend much more vigorous policy responses. This paper attempts to match the historical policy rule with an optimal policy rule by incorporating uncertainty into the derivation of the optimal rule and by examining plausible variations in the policymaker's model and preferences.

This paper explores the effect of research and development (R&D) and capital on factor intensity and skill bias in a sample of manufacturing plants. Firm and industry R&D as well as plant level capital increase the factor intensity of labor over materials. In contrast, skill bias originates in portions of capital and R&D. Equipment capital and firm R&D in the same product as a plant are consistently skill biased, while structures are biased against skill. Furthermore, general firm and industry R&D increase investment in equipment but not structures. This shows that the skill bias of R&D occurs through two distinct channels. First, firm R&D specific to the product increases the relative demand for skilled labor directly and in the short run through the cost function. Second, general firm and industry R&D exert an additional skill bias by favoring equipment over structures in the long run, demonstrating the broader compass of the skill bias of R&D over time.

The paper is concerned with developing a production theory for the case when some inputs have nonlinear prices because the price depends on endogenous quality. This involves extending the notion of a cost function to the case where nonlinear prices are parameters of costs. After developing the appropriate theory, we apply our results to the case of coal-fired electric power generation where fuel quality depends on sulfur and ash impurities. Environmental regulations induce a negative value on sulfur whereas ash impurities degrade performance and thus reduce production possibilities. A number of empirical results emerge, including significant rates of technological change that are sulfur and ash saving though capital using. This change may explain in part the recent drop in the price of sulfur allowances in the United States.

The paper considers the estimation of welfare measures when the functional form of demand is unknown. An adaptation of an argument of Gallant (1987) is used to show that welfare estimators based on a Fourier functional form for demand will be consistent under weak assumptions. Simulation evidence is presented for equivalent variation. True demand is a generalized Box–Cox function, estimated demand is a Fourier form, and equivalent variation is estimated by applying Vartia's (1983) algorithm to the estimated demand function. The estimator of equivalent variation has small asymptotic bias in the case of the assumed family of data generating processes.