The vast majority of existing studies that estimate the average unexplained gender pay gap use unnecessarily restrictive linear versions of the Blinder-Oaxaca decomposition. Using a notably rich and large data set of 1.7 million employees in Switzerland, we investigate how the methodological...

The vast majority of existing studies that estimate the average unexplained gender pay gap use unnecessarily restrictive linear versions of the Blinder-Oaxaca decomposition. Using a notably rich and large data set of 1.7 million employees in Switzerland, we investigate how the methodological...

The vast majority of existing studies that estimate the average unexplained gender pay gap use unnecessarily restrictive linear versions of the Blinder-Oaxaca decomposition. Using a notably rich and large data set of 1.7 million employees in Switzerland, we investigate how the methodological...

Abstract The estimation of causal effects is fundamental in situations where the underlying system will be subject to active interventions. Part of building a causal inference engine is defining how variables relate to each other, that is, defining the functional relationship between variables...

The vast majority of existing studies that estimate the average unexplained gender pay gap use unnecessarily restrictive linear versions of the Blinder-Oaxaca decomposition. Using a notably rich and large data set of 1.7 million employees in Switzerland, we investigate how the methodological...

The vast majority of existing studies that estimate the average unexplained gender pay gap use unnecessarily restrictive linear versions of the Blinder-Oaxaca decomposition. Using a notably rich and large data set of 1.7 million employees in Switzerland, we investigate how the methodological...

The vast majority of existing studies that estimate the average unexplained gender pay gap use unnecessarily restrictive linear versions of the Blinder-Oaxaca decomposition. Using a notably rich and large data set of 1.7 million employees in Switzerland, we investigate how the methodological...

Oil market VAR models have become the standard tool for understanding the evolution of the real price of oil and its impact in the macro economy. As this literature has expanded at a rapid pace, it has become increasingly difficult for mainstream economists to understand the differences between...

There exists significant hype regarding how much machine learning and incorporating social media data can improve forecast accuracy in commercial applications. To assess if the hype is warranted, we use data from the film industry in simulation experiments that contrast econometric approaches...

There exists significant hype regarding how much machine learning and incorporating social media data can improve forecast accuracy in commercial applications. To assess if the hype is warranted, we use data from the film industry in simulation experiments that contrast econometric approaches...

Oil market VAR models have become the standard tool for understanding the evolution of the real price of oil and its impact in the macro economy. As this literature has expanded at a rapid pace, it has become increasingly difficult for mainstream economists to understand the differences between...

Many financial decisions, such as portfolio allocation, risk management, option pricing and hedge strategies, are based on forecasts of the conditional variances, covariances and correlations of financial returns. The paper shows an empirical comparison of several methods to predict...

Many financial decisions, such as portfolio allocation, risk management, option pricing and hedge strategies, are based on forecasts of the conditional variances, covariances and correlations of financial returns. The paper shows an empirical comparison of several methods to predict...

System dynamics and econometrics have traditionally been seen as contrasting and sometimes conflicting approaches for deriving parameters for economic models. System dynamics as a simulation method uses repeated runs to achieve calibration through optimisation, whereas simulation as an...

Linear regression is a powerful tool for investigating the relationships between multiple variables by relating one variable to a set of variables. It can identify the effect of one variable while adjusting for other observable differences. For example, it can analyze how wages relate to gender,...

Linear regression is a powerful tool for investigating the relationships between multiple variables by relating one variable to a set of variables. It can identify the effect of one variable while adjusting for other observable differences. For example, it can analyze how wages relate to gender,...

Managers of businesses that involve agricultural commodities need price forecasts in order to manage the risk in either the sale or purchase of agricultural commodities. Sometimes the most important forecasting component is simply whether the price will move up or down. Such binary forecasts are...

This paper provides a description of Istat’s new Macroeconometric Model MeMo-It. This is the tool used by Istat to produce bi-annual medium-term forecasts of the Italian economy since May 2012. The key model’s features are illustrated and compared with other modeling approaches used in the...

This note demonstrates that in applied regression analysis, the variance of a coefficient of interest may decrease from the inclusion of a control variable, contrasting with Clarke’s assertion (2005, 2009) that the variance can only increase or stay the same. Practitioners may thus be well...

In this reply, I salute the correction, replication, and extensions carried out by David Findlay and John Santos (2012) based on my jointly authored paper Hewitt, Muñoz, Oliver, and Regoli (2005). I expound briefly on why, even though we and they have found no statistically significant...

This is a supplement to “Race, Ethnicity, and Baseball Card Prices: A Replication, Correction, and Extension of Hewitt, Muñoz, Oliver, and Regoli” in which we investigate the effects of career performance, card quality and availability, and player race and ethnicity on baseball card prices....

Using a sample of all-time great baseball players, we investigate the effects of career performance, card quality and availability, and player race and ethnicity on baseball card prices. We estimate various specifications of the card price equations used by Hewitt, Muñoz, Oliver, and Regoli...

As a contribution to further development of the stochastic frontier methodology the specification method for a 3-factor stochastic model of the production potential of a company is given. Along with labor input and physical capital input we consider intellectual capital as a basic production...

In this paper we develop a testing and modelling procedure for describing the long-term volatility movements over very long return series. For the purpose, we assume that volatility is multiplicatively decomposed into a conditional and an unconditional component as in Amado and Teräsvirta...

In this paper we develop a testing and modelling procedure for describing the long-term volatility movements over very long return series. For the purpose, we assume that volatility is multiplicatively decomposed into a conditional and an unconditional component as in Amado and Teräsvirta...

This note demonstrates that in applied regression analysis, the variance of a coefficient of interest may decrease from the inclusion of a control variable, contrasting with Clarke's assertion (2005, 2009) that the variance can only increase or stay the same. Practitioners may thus be well...

Performance of unit root tests depends on several specification decisions prior to their application, e.g., whether or not to include a deterministic trend. Since there is no standard procedure for making such decisions; therefore, the practitioners routinely make several arbitrary specification...

This note demonstrates that in applied regression analysis, the variance of a coefficient of interest may decrease from the inclusion of a control variable, contrasting with Clarke's assertion (2005, 2009) that the variance can only increase or stay the same. Practitioners may thus be...

Performance of unit root tests depends on several specification decisions prior to their application, e.g., whether or not to include a deterministic trend. Since there is no standard procedure for making such decisions; therefore, the practitioners routinely make several arbitrary specification...

In this article we introduce and evaluate testing procedures for specifying the number k of nearest neighbours in the weights matrix of spatial econometric models. The spatial J-test is used for specification search. Two testing procedures are suggested: an increasing neighbours testing...

This article assesses how the form of the utility function in discrete-choice experiments (DCEs) affects estimates of willingness-to-pay (WTP). The utility function is usually assumed to be linear in its attributes. Non-linearities, in the guise of interactions and higher-order terms, are...

The problem of statistical model specification was initially raised by R.A. Fisher who understood it as an informed selection whose adequacy is testable a posteriori. This, however, raised the problem of how to blend substantive subject matter with statistical information in empirical modeling,...

Recent studies provide strong statistical evidence challenging the existence of out-of-sample return predictability. The economic significance of return predictability is also controversial. In this paper, we find significant economic gains for dynamic trading strategies based on return...

The relative role of economic growth vis-a-vis public action in raising living standards in developing countries has been a point of contention for quite some time now. The arguments on both sides are usually based on some estimated relationship between indicators of living standard and other...