This paper provides new identification results for a large class of (static) consumer problems that contain (production) functions in the budget constraints. I show that the mere structure of the consumer problem is sufficient to nonparametrically identify the part of the production functions...

We present a unifying identification strategy of dynamic average treatment effect parameters for staggered interventions when parallel trends are valid only after controlling for interactive fixed effects. This setting nests the usual parallel trends assumption, but allows treated units to have...

While applications of big data analytics have brought many new opportunities to economic research, with datasets containing tens of millions of observations, making usual econometric inferences based on extreme estimators would require huge computing powers and memories that are often not...

In recent years, there has been substantive empirical evidence that stochastic volatility is rough. In other words, the local behavior of stochastic volatility is much more irregular than semimartingales and resembles that of a fractional Brownian motion with Hurst parameter H0.5. In this paper,...

Maximum Likelihood (ML) shows both lower power and higher bias in small sample Monte Carlo experiments than Indirect Inference (II) and IIís higher power comes from its use of the model-restricted distribution of the auxiliary model coeffi cients (Le et al. 2016). We show here that IIís higher...

A common practice in estimating parameters in DSGE models is to Önd a set that when simulated gets close to an average of certain data moments; the modelís simulated performance for other moments is then compared to the data for these as an informal test of the model. We call this procedure...