We report a portfolio-choice experiment that enables us to estimate parametric models of ambiguity aversion at the level of the individual subject. The assets are Arrow securities that correspond to three states of nature, where one state is risky with known probability and two states are ambiguous with unknown probabilities. We estimate two specifications of ambiguity aversion, one kinked and one smooth, that encompass many of the theoretical models in the literature. Each specification includes two parameters: one for ambiguity attitudes and another for risk attitudes. We also estimate a three-parameter specification that includes an additional parameter for pessimism/optimism (underweighting/overweighting the probabilities of different payoffs). The parameter estimates for individual subjects exhibit considerable heterogeneity. We cannot reject the null hypothesis of subjective expected utility for a majority of subjects. Most of the remaining subjects exhibit statistically significant ambiguity aversion or seeking and/or pessimism or optimism.

]]>Fertility in the United States rose from a low of 2.27 children for women born in 1908 to a peak of 3.21 children for women born in 1932. It dropped to a new low of 1.74 children for women born in 1949, before stabilizing for subsequent cohorts. We propose a novel explanation for this boom–bust pattern, linking it to the huge improvements in maternal health that started in the mid-1930s. Our hypothesis is that the improvements in maternal health contributed to the mid-twentieth century baby boom and generated a rise in women's human capital, ultimately leading to a decline in desired fertility for subsequent cohorts. To examine this link empirically, we exploit the large cross-state variation in the magnitude of the decline in pregnancy-related mortality and the differential exposure by cohort. We find that the decline in maternal mortality is associated with a rise in fertility for women born between 1921 and 1940, with a rise in college and high school graduation rates for women born in 1933–1950 relative to previous cohorts, and with a decline in fertility for women born in 1941–1950 relative to those born in 1921–1940. The analysis provides new insights on the determinants of fertility in the United States and other countries that experienced similar improvements in maternal health.

]]>The control function approach (Heckman and Robb (1985)) in a system of linear simultaneous equations provides a convenient procedure to estimate one of the functions in the system using reduced form residuals from the other functions as additional regressors. The conditions on the structural system under which this procedure can be used in nonlinear and nonparametric simultaneous equations has thus far been unknown. In this paper, we define a new property of functions called *control function separability* and show it provides a complete characterization of the structural systems of simultaneous equations in which the control function procedure is valid.

This paper develops a model according to which the costs of business cycles are nontrivial because they reduce the average level of output. The reason is an *interaction* between job creation costs and an agency problem. The agency problem triggers separations during economic downturns even though both the employer and the worker would be better off if the job was not discontinued, that is, affected jobs have strictly positive surplus values. Similarly, booms make it possible for more jobs to overcome the agency problem. These effects do not offset each other, because business cycles reduce the expected job duration for these jobs. With positive job creation costs, business cycles then reduce the creation of valuable jobs and lower average activity levels. Considering a wide range of parameter values, we find estimates for the cost of business cycles ranging from 2.03% to 12.7% of gross domestic product.

In a real effort experiment with repeated competition we find striking differences in how the work effort of men and women responds to previous wins and losses. For women, losing per se is detrimental to productivity, but for men, a loss impacts negatively on productivity only when the prize at stake is big enough. Responses to luck are more persistent and explain more of the variation in behavior for women, and account for about half of the gender performance gap in our experiment. Our findings shed new light on why women may be less inclined to pursue competition-intensive careers.

]]>In France, firms that have 50 employees or more face substantially more regulation than firms that have less than 50. As a result, the size distribution of firms is visibly distorted: there are many firms with exactly 49 employees. We model the regulation as the combination of a sunk cost that must be paid the first time the firm reaches 50 employees and a payroll tax that is paid each period thereafter when the firm operates with more than 50 employees. We estimate the model using indirect inference by fitting the discontinuity of the size distribution. The key finding is that the regulation is equivalent to a combination of a sunk cost approximately equal to about 1 year of an average employee salary and a small payroll tax of 0.04%. Our structural model fits well the discontinuity in the size distribution. Removing the regulation improves labor allocation across firms, leading in steady state to an increase in output per worker slightly less than 0.3%, holding the number of firms fixed. However, if firm entry is elastic, the steady-state gains are an order of magnitude smaller.

]]>In firms with concentrated ownership the controlling shareholder may pursue nonmonetary private returns, such as electoral goals in a firm controlled by politicians or family prestige in family firms. We use a simple theoretical model to analyze how this mechanism affects the selection of executives and, through this, the firm's productivity compared to a benchmark where the owner only cares about the value of the firm. We discuss identification and derive two structural estimates of the model, based on different sample moments. The estimates, based on a matched employer–employee data set of Italian firms, suggest that private returns are larger in family- and government-controlled firms than in firms controlled by a conglomerate or by a foreign entity. The resulting distortion in executive selection can account for total factor productivity differentials between control types of up to 10%.

]]>This paper considers inference in log-linearized dynamic stochastic general equilibrium (DSGE) models with weakly (including un-) identified parameters. The framework allows for analysis using only part of the spectrum, say at the business cycle frequencies. First, we characterize weak identification from a frequency domain perspective and propose a score test for the structural parameter vector based on the frequency domain approximation to the Gaussian likelihood. The construction heavily exploits the structures of the DSGE solution, the score function, and the information matrix. In particular, we show that the test statistic can be represented as the explained sum of squares from a complex-valued Gauss–Newton regression, where weak identification surfaces as (imperfect) multicollinearity. Second, we prove that asymptotically valid confidence sets can be obtained by inverting this test statistic and using chi-squared critical values. Third, we provide procedures to construct uniform confidence bands for the impulse response function, the time path of the variance decomposition, the individual spectrum, and the absolute coherency. Finally, a simulation experiment suggests that the test has adequate size even with relatively small sample sizes. It also suggests it is possible to have informative confidence sets in DSGE models with unidentified parameters, particularly regarding the impulse response functions. Although the paper focuses on DSGE models, the methods are applicable to other dynamic models with well defined spectra, such as stationary (factor-augmented) vector autoregressions.

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