An exciting development in empirical macroeconometrics is the increasing use of external sources of as-if randomness to identify the dynamic causal effects of macroeconomic shocks. This approach - the use of external instruments - is the time series counterpart of the highly successful strategy...

Many applications in financial economics use data series with different starting or ending dates. This paper describes estimation methods, based on the generalized method of moments (GMM), which make use of all available data for each moment condition. We introduce two asymptotically equivalent...

We propose a local measure of the relationship between parameter estimates and the moments of the data they depend on. Our measure can be computed at negligible cost even for complex structural models. We argue that reporting this measure can increase the transparency of structural estimates,...

Models defined by moment inequalities have become a standard modeling framework for empirical economists, spreading over a wide range of fields within economics. From the point of view of an empirical researcher, the literature on inference in moment inequality models is large and complex,...

Food Stamps represent nearly $11 billion of personal income in the United States. The coupons that are issued to represent the purchasing power available to recipients are also reserves for the commercial banking system.This study asks how closely these coupons are substitutable for what is...

Momentum in individual stock returns emanates from momentum in factor returns. Most factors are positively autocorrelated: the average factor earns a monthly return of 1 basis point following a year of losses and 53 basis points following a positive year. Factor momentum explains all forms of...

The SVAR and narrative approaches to estimating tax multipliers deliver significantly different results. The former yields multipliers of about 1 percent, whereas the latter produces much larger multipliers of about 3 percent. The SVAR and narrative approaches differ along two important...

We propose a discrete-time stochastic volatility model in which regime switching serves three purposes. First, changes in regimes capture low frequency variations, which is their traditional role. Second, they specify intermediate frequency dynamics that are usually assigned to smooth...