Research Database

This paper proposes an aggregative model of Total Factor Productivity (TFP) in the spirit of Houthakker (1955–1956). It considers a frictional labor market where production units are subject to idiosyncratic shocks and jobs are created and destroyed as in Mortensen and Pissarides (1994). An aggregate production function is derived by aggregating across micro production units in equilibrium. The level of TFP is explicitly shown to depend on the underlying distribution of shocks as well as on all the characteristics of the labor market as summarized by the job-destruction decision. The model is also used to study the effects of labor-market policies on the level of measured TFP.

We develop a model of gross job and worker flows and use it to study how the wages, permanent incomes, and employment status of individual workers evolve over time. Our model helps explain various features of labor markets, such as the amount of worker turnover in excess of job reallocation, the length of job tenures and unemployment duration, and the size and persistence of the changes in income that workers experience due to displacements or job-to-job transitions. We also examine the effects that labor market institutions and public policy have on the gross flows, as well as on the resulting wage distribution and employment in the equilibrium. From a theoretical standpoint, we propose a notion of competitive equilibrium for random matching environments, and study the extent to which it achieves an efficient allocation of resources.

Previous research has suggested that discrete and occasional plant-level capital adjustments have significant aggregate implications. In particular, it has been argued that changes in plants’ willingness to invest in response to aggregate shocks can at times generate large movements in total investment demand. In this study, I re-assess these predictions in a general equilibrium environment. Specifically, assuming nonconvex costs of capital adjustment, I derive generalized (S,s) adjustment rules yielding lumpy plant-level investment within an otherwise standard equilibrium business cycle model. In contrast to previous partial equilibrium analyses, model results reveal that the aggregate effects of lumpy investment are negligible. In general equilibrium, households’ preference for relatively smooth consumption profiles offsets changes in aggregate investment demand implied by the introduction of lumpy plant-level investment. As a result, adjustments in wages and interest rates yield quantity dynamics that are virtually indistinguishable from the standard model.

This paper studies the empirical relevance of temptation and self-control using household-level data from the Consumer Expenditure Survey. We estimate an infinite-horizon consumption-savings model that allows, but does not require, temptation and self-control in preferences. To help identify the presence of temptation, we exploit an implication of the theory that a tempted individual has a preference for commitment. In the presence of temptation, the cross-sectional distribution of the wealth-consumption ratio, in addition to that of consumption growth, becomes a determinant of the asset-pricing kernel, and the importance of this additional pricing factor depends on the strength of temptation. The estimates that we obtain provide statistical evidence supporting the presence of temptation. Based on our estimates, we explore some quantitative implications of this class of preferences on equity premium and on the welfare cost of business cycles.

In recent financial crises and in recent theoretical studies of them, abrupt declines in capital inflows, or sudden stops, have been linked with large drops in output. Do sudden stops cause output drops? No, according to a standard equilibrium model in which sudden stops are generated by an abrupt tightening of a country’s collateral constraint on foreign borrowing. In this model, in fact, sudden stops lead to output increases, not decreases. An examination of the quantitative effects of a well-known sudden stop, in Mexico in the mid-1990s, confirms that a drop in output accompanying a sudden stop cannot be accounted for by the sudden stop alone. To generate an output drop during a financial crisis, as other studies have done, the model must include other economic frictions which have negative effects on output large enough to overwhelm the positive effect of the sudden stop.

We find that in a sample of emerging economies business cycles are more volatile than in developed ones, real interest rates are countercyclical and lead the cycle, consumption is more volatile than output and net exports are strongly countercyclical. We present a model of a small open economy, where the real interest rate is decomposed in an international rate and a country risk component. Country risk is affected by fundamental shocks but, through the presence of working capital, also amplifies the effects of those shocks. The model generates business cycles consistent with Argentine data. Eliminating country risk lowers Argentine output volatility by 27% while stabilizing international rates lowers it by less than 3%.

Arrow (1962) argued that since a monopoly restricts output relative to a competitive industry, it would be less willing to pay a fixed cost to adopt a new technology. Arrow’s idea has been challenged and critiques have shown that under different assumptions, increases in competition lead to less innovation. We develop a new theory of why a monopolistic industry innovates less than a competitive industry. The key is that firms often face major problems in integrating new technologies. In some cases, upon adoption of technology, firms must temporarily reduce output. We call such problems switchover disruptions. If firms face switchover disruptions, then a cost of adoption is the forgone rents on the sales of lost or delayed production, and these opportunity costs are larger the higher the price on those lost units. In particular, with greater monopoly power, the greater the forgone rents. This idea has significant consequences since if we add switchover disruptions to standard models, then the critiques of Arrow lose their force: competition again leads to greater adoption. In addition, we show that our model helps explain the accumulating evidence that competition leads to greater adoption (whereas the standard models cannot).

Recent empirical analysis has found nonlinearities to be important in understanding aggregated investment. Using an equilibrium business cycle model, we search for aggregate nonlinearities arising from the introduction of nonconvex capital adjustment costs. We find that, while such costs lead to nontrivial nonlinearities in aggregate investment demand, equilibrium investment is effectively unchanged. Our finding, based on a model in which aggregate fluctuations arise through exogenous changes in total factor productivity, is robust to the introduction of shocks to the relative price of investment goods.

We study inferences about the dynamics of labor adjustment obtained by the “gap methodology” of Caballero and Engel [1993] and Caballero, Engel and Haltiwanger [1997]. In that approach, the policy function for employment growth is assumed to depend on an unobservable gap between the target and current levels of employment. Using time series observations, these studies reject the partial adjustment model and find that aggregate employment dynamics depend on the cross-sectional distribution of employment gaps. Thus, nonlinear adjustment at the plant level appears to have aggregate implications. We argue that this conclusion is not justified: these findings of nonlinearities in time series data may reflect mismeasurement of the gaps rather than the aggregation of plant-level nonlinearities.

Manufacturing plants have a clear life cycle: they are born small, grow substantially as they age, and eventually die. Economists have long thought that this life cycle is driven by the accumulation of plant-specific knowledge, here called organization capital. Theory suggests that where plants are in the life cycle determines the size of the payments, or dividends, plant owners receive from organization capital. These payments are compensation for the interest cost to plant owners of waiting for their plants to grow. We build a quantitative growth model of the life cycle of plants and use it, along with U.S. data, to infer the overall size of these payments. They turn out to be quite large—more than one-third the size of the payments plant owners receive from physical capital, net of new investment, and more than 40% of payments from all forms of intangible capital.