Showing 1 - 10 of 202
Statistical inference can be described as the process of drawing conclusions about a population or process based on sample data. This chapter outlines the logic of “classical” or “frequentist” methods for such inference. Three commonly used concepts for assessing statistical error are...
Persistent link: https://www.econbiz.de/10014100750
This paper discusses causal inference techniques for social scientists through the lens of applied microeconomics. We frame causal inference using the standard of the ideal experiment, emphasizing problems of omitted variable bias and reverse causality. We explore how laboratory and field...
Persistent link: https://www.econbiz.de/10012908420
What is Statistics? Opinions vary. In fact, there is a continuous spectrum of attitudes toward statistics ranging from pure theoreticians, proving asymptotic efficiency and searching for most powerful tests, to wild practitioners, blindly reporting p-values and claiming statistical significance...
Persistent link: https://www.econbiz.de/10012927199
In this paper, I try to tame "Basu's elephants" (data with extreme selection on observables). I propose new practical large-sample and finite-sample methods for estimating and inferring heterogeneous causal effects (under unconfoundedness) in the empirically relevant context of limited overlap....
Persistent link: https://www.econbiz.de/10014262361
The instrumental variable model is one of the central tools for the analysis of causal relationships in observational data. The Anderson and Rubin (1949) test is an important method that allows for reliable inference in the instrumental variable model when the instruments are weak. Yet, the...
Persistent link: https://www.econbiz.de/10013210938
This paper considers the problem of deriving heteroskedasticity and autocorrelation robust (HAR) inference about a scalar parameter of interest. The main assumption is that there is a known upper bound on the degree of persistence in data. I derive finite‐sample optimal tests in the Gaussian...
Persistent link: https://www.econbiz.de/10015190109
We propose the double robust Lagrange multiplier (DRLM) statistic for testing hypotheses specified on the minimizer of the population continuous updating objective function. The (bounding) χ2 limiting distribution of the DRLM statistic is robust to both misspecification and weak identification,...
Persistent link: https://www.econbiz.de/10015190343
This paper argues that the current way in which the undergraduate introductory econometrics course is taught is neither inline with current empirical practice nor very intuitive. It proposes a shift in focus of the course on causal inference using the Roy-Rubin Causal Model (RRCM). A second...
Persistent link: https://www.econbiz.de/10013144775
We study semi-parametric estimation and inference in cointegrated panels with endogenous feedback, allowing for general time-series and cross-section dependence and heterogeneity.Central to this literature are the fully-modified OLS of Phillips and Hansen (1990) that use a spectral...
Persistent link: https://www.econbiz.de/10012970628
Marketing applications offer many difficult and unique challenges in causal inference. In particular, targeted marketing activities, the arch-typical example of is search ads, can be difficult to evaluate using purely observational data. I review causal methods proposed in the recent...
Persistent link: https://www.econbiz.de/10012948022