Given data on a scalar random variable 𝑌, a prediction set for 𝑌 with miscoverage level 𝛼 is a set of values for 𝑌 that contains a randomly drawn 𝑌 with probability 1 - 𝛼, where 𝛼 ∈ (0, 1). Among all prediction sets that satisfy this coverage property, the oracle...

When estimating the effects of treatments defined by complex formulas, researchers often use simple functions of exogenous shocks as instruments. A leading example is "simulated instruments" for public policy eligibility, which capture variation in state-level policy generosity. We show how more...

We develop a new approach to estimating flexible demand models with exogenous supply-side shocks. Our approach avoids conventional assumptions of exogenous product characteristics, putting no restrictions on product entry, despite using instrumental variables that incorporate characteristic...

We propose a flexible, extensible family of distributions for testing Markov Chain Monte Carlo implementations. Distributions are created by nesting simple transformations, which allow various shapes, including multiple modes and fat tails. The resulting distributions can be sampled with high...

Purpose - Developing price forecasts for various agricultural commodities has long been a significant undertaking for a variety of agricultural market players. The weekly wholesale price of edible oil in the Chinese market over a ten-year period, from January 1, 2010 to January 3, 2020, is the...

This paper analyzes how interaction effects can be consistently estimated under economically plausible assumptions in linear panel models with a fixed Tdimension. We advocate for a correlated interaction term estimator (CITE) and show that it is consistent under conditions that are not...

Purpose - The authors' conclusions are based on mathematical derivations that are supported by computer simulations and three worked examples in applications of economics and finance. Finally, the authors provide a link to a computer program so that researchers can perform the analyses easily....

When estimating the effects of treatments defined by complex formulas, researchers often use simple functions of exogenous shocks as instruments. A leading example is "simulated instruments" for public policy eligibility, which capture variation in state-level policy generosity. We show how more...

We develop a new approach to estimating flexible demand models with exogenous supply-side shocks. Our approach avoids conventional assumptions of exogenous product characteristics, putting no restrictions on product entry, despite using instrumental variables that incorporate characteristic...

In this paper we study a class of weighted estimands, which we define as parameters that can be expressed as weighted averages of the underlying heterogeneous treatment effects. The popular ordinary least squares (OLS), two-stage least squares (2SLS), and two-way fixed effects (TWFE) estimands...

Several process parameters affect product reliability. Traditional reliability improvement methods primarily focus on maximizing product lifetime, often overlooking the variation in product lifetime. Manufacturers, however, aim to produce products with minimal variations in their performance....

Contrary to claims in studies on financial economics, a sparse database often obscures the identification of parameters in macroeconomic models. These identification problems originate from the poorly defined mapping between a structural model and reduced-form parameters. Hence, researchers rely...

We investigate a bracketing property that purports to yield upper- and lower bounds on the treatment effects obtained from a fixed effects- and lagged dependent variable model. Referencing both analytical results and a Monte Carlo simulation, we explore the conditions under which the bracketing...

We argue that measurement error in historical price data has led researchers to erroneously believe that there was little persistence of inflation during the 19th century. Using a statistical technique that accounts for these errors, we estimate the persistence of (a) US inflation and (b)...

Regressors often have heterogeneous effects in the social sciences, implying unit-specific slopes. OLS is frequently applied to these correlated coefficient models. I first show that without restrictions on the relation between slopes and regressors, OLS estimates can take any value including...

This paper proposes a subsampling inference method for extreme conditional quantiles based on a self-normalized version of a local estimator for conditional quantiles, such as the local linear quantile regression estimator. The proposed method circumvents difficulty of estimating nuisance...

Bessel's correction adjusts the denominator in the sample variance formula from n to n − 1 to produce an unbiased estimator for the population variance. This paper includes rigorous derivations, geometric interpretations, and visualizations. It then introduces the concept of "bariance," an...

Many panel data methods, while allowing for general dependence between covariates and time-invariant agent-specific heterogeneity, place strong a priori restrictions on feedback: how past outcomes, covariates, and heterogeneity map into future covariate levels. Ruling out feedback entirely, as...

Algorithms are increasingly used to aid with high-stakes decision making. Yet, their predictive ability frequently exhibits systematic variation across population subgroups. To assess the trade-off between fairness and accuracy using finite data, we propose a debiased machine learning estimator...

Structural estimation in economics often makes use of models formulated in terms of moment conditions. While these moment conditions are generally well-motivated, it is often unknown whether the moment restrictions hold exactly. We consider a framework where researchers model their belief about...

Beta regression is a valuable statistical technique for modeling response variables within the standard unit interval (0, 1), where values represent rates, proportions, or probabilities. However, outliers in beta regression can severely impact parameter estimates and model performance, leading...

This paper uses firm level data from the World Bank Enterprise surveys conducted in 2019 and from the COVID-19 follow-up surveys conducted in 2020 in eight European countries to investigate the link between firm characteristics before the pandemic and firm survival until 2020. For the first time...

This paper studies linear time‐series regressions with many regressors. Weak exogeneity is the most used identifying assumption in time series. Weak exogeneity requires the structural error to have zero conditional expectation given present and past regressor values, allowing errors to...

In this paper, we analyze regressions with observations collected at small time intervals over a long period of time. For the formal asymptotic analysis, we assume that samples are obtained from continuous time stochastic processes, and let the sampling interval δ shrink down to zero and the...

The use of renewable energy, such as solar power, has the potential to mitigate the negative impacts of fossil fuel consumption. West Java Province holds significant potential for solar-based electricity development. This study aims to estimate hourly solar radiation, addressing extreme...

This paper puts forward a general statistical model in the time domain based on the concept of fractional integration. More specifically, in the proposed framework instead of imposing that the roots are strictly on the unit circle, we also allow them to be within the unit circle. This approach...

This note puts forward a new modelling approach that includes both fractional integration and autoregressive processes in a unified framework. The proposed model is very general and includes other more standard approaches such as the AR(F)IMA models. Some Monte Carlo evidence shows that the...

The most widely used textbooks today conflate three distinct population parameters: the population regression function (PRF), the conditional expectation function (CEF), and the causal effect. They also incorrectly suggest, and sometimes state, that the Conditional Mean Zero assumption implies...