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...

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...

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...

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...

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...

This paper proposes a model that explains both recently documented facts about the decline of disruptive innovation and the decline in productivity growth as the result of large firms trying to monopolize technologies by poaching inventors from disruptive activities. To come to this conclusion,...

Behavioral economics provides a rich set of explicit models of non-classical preferences and belief formation which can be used to estimate structural models of decision making. At the same time, experimental approaches allow the researcher to exogenously vary components of the decision making...

We use a behavioural microsimulation model embedded in a numerical optimization procedure in order to identify optimal (social welfare maximizing) tax-transfer rules. We consider the class of tax-transfer rules consisting of a universal basic income and a tax defined by a 4th degree polynomial....

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.

Preface Part 1. The ordinary least square estimator 1. Simple linear regression model 2. Statistical properties of the simple linear estimator 3. Multiple Regression Model 4. Interpretation of the Coefficients Part 2. Beyond the OLS estimator 5. Maximum likelihood estimator 6. Non-spherical...

Globalization and automation might imply deep changes on the labour market. An important policy issue is whether and how the tax-transfer rules should be reformed to cope with those changes. While the prevailing response has consisted of more sophisticated designs of mean-testing and targeting,...

This study involved conducting a survival analysis by fitting a Cox proportional hazards model to Korea Labor Panel data to analyze the impact of parental job loss on children's delayed admission to colleges and universities in South Korea, using 376 subjects whose parental education levels were...

This paper formulates and estimates a rigorously-justified linear probability model of binary choices over alternatives characterized by unobserved attributes. The model is applied to estimate preferences of congressmen as expressed in their votes on bills. The effective dimension of the...

Full suppression strategies remain the dominant option in wildfire management, despite a large body of research demonstrating the ecological and economic benefits of allowing unplanned wildfires to burn under favorable conditions. Consequently, empirical research identifying and understanding...

We propose new difference-in-difference (DID) estimators for treatments continuously distributed at every time period, as is often the case of trade tariffs, or temperatures. We start by assuming that the data only has two time periods. We also assume that from period one to two, the treatment...

I propose a method for estimating treatment effect heterogeneity in event studies with staggered adoption. This method serves as an alternative to two-way fixed effects regressions, which have been shown to be near-term biased in these settings. I build on insights from the machine learning (ML)...

This paper considers the evaluation of the average treatment effect of a binary endogenous regressor on a binary outcome when one imposes a threshold crossing model on both the endogenous regressor and the outcome variable but without imposing parametric functional form or distributional...

Misclassification of a binary response variable and nonrandom sample selection are data issues frequently encountered by empirical researchers. For cases in which both issues feature simultaneously in a data set, we formulate a sample selection model for a misclassified binary outcome in which...