This article estimates the impact of a policy change on an event probability in a difference-in-differences hazard model using four estimators. We examine the error distributions of the estimators via a simulation experiment with twelve different scenarios. In four simulation scenarios when all...

This article introduces new counterfactual standardization techniques for comparing duration distributions subject to random censoring through counterfactual decompositions. The counterfactual distribution of one population relative to another is computed after estimating the conditional...

Discrimination against women in agricultural decision-making is a major threat to the empowerment of women in many developing countries where agriculture is not only the major source of livelihood, at times the only source of livelihood. It hampers their socio-economic status as well as the...

Analyzing survival (life-testing) data and drawing inferences about them is a part of engineering and health sciences. So far, various statistical tools, e.g., survival (reliability) function (s f ), probability density function (pd f ), and hazard rate function (HR) were available among...

Using a rich and unique combined administrative-survey dataset, this paper explores how sensitive propensity score (PS) matching estimates of Active Labor Market Policies (ALMPs) based on the selection-on-observables assumption are to typically unobserved covariates. Using a sample of German...

The properties of classical panel data estimators including fixed effect, first-differences, random effects, and generalized method of moments-instrumental variables estimators in both static as well as dynamic panel data models are investigated under sample selection. The correlation of the...

We revisit the finite-sample behavior of just-identified instrumental variables (IV) estimators, arguing that in most microeconometric applications, just-identified IV bias is negligible and the usual inference strategies likely reliable. Three widely-cited applications are used to explain why...

For difference-in-differences methods, there has been great attention to obtaining consistent estimates of treatment effects, especially when the treatment effects are heterogeneous. However, there has been little discussion of the importance of weights in aggregating those treatment effects...

1. General Introduction -- 2. Dynamics in Econometrics -- 3. Estimating the Model -- 4. Testing the Model -- 5. Non-Stationarity and Cointegration -- 6. Specifying the ARDL Model -- 7. Vector Autoregressions -- 8. Panel Data Models -- 9. Non-Stationary Panels -- 10. The Binary Qualitative Model.

"This book is about doing microeconometrics, defined by Cameron and Trivedi (2005) as the analysis of individual-level data on the economic behavior of individuals or firms using regression methods applied to cross-section and panel data with R. Microeconometrics became increasingly popular in...

his thesis consists of three independent chapters. Each chapter analyzes the equilibrium outcomes of the labor and housing market by describing the behavior of the participants in the markets by the perturbed utility model. This class of models allows for a more general substitution patterns as...