A review of production function research with telecommunications data shows strong scale economies, which is supported by more recent advances in production function econometrics. Newer economics of reputation and competition shows that both moral hazard and adverse selection problems are...

Nonlinear nonparametric statistics (NNS) algorithm offers new tools for curve fitting. A relationship between k-means clustering and NNS regression points is explored with graphics showing a perfect fit in the limit. The goal of this paper is to demonstrate NNS as a form of unsupervised...

Liberal think tanks claim that low growth in US wages is reducing incentives for labor-saving innovation and hence creating low labor productivity. Since conservatives reject this, a recent New York Times article stated that economists have a "chicken or egg problem" here. This paper uses modern...

Since causal paths are important for all sciences, my package 'generalCorr' provides sophisticated R functions using four orders of stochastic dominance and generalized partial correlation coefficients. A new test (in Version 1.0.3) replaces Hausman-Wu medieval-style diagnosis of endogeneity...

Usual correlations assume linearity. If new generalized correlations satisfy r*(Y |X) r*(X|Y ), X better predicts Y than vice versa. Then we say that X "causes" Y . Thus, Vinod (2013) revives Granger's instantaneous causality concept. Mooij et al. (2014) and their references seem unaware of...

Statistically dependent X and Y have conditional density f(Y|X) asymmetrically different from unconditional f(Y). Theorem 1 com- pares two flipped kernel regressions to derive necessary conditions for causal path X -- Y and exogeneity meaning that X is self-driven. Hausman-Wu's indirect...

When does an entire income distribution f(x2) dominate f(x1)? When can we comprehensively say that f(x2) is ``richer'' than f(x1)? Anderson (1996) proposed a nonparametric quantification for pair-wise welfare-ordering of two countries by their entire income distributions. His algorithm readily...

Quantitative researchers often use Student’s t-test (and its p-values) to claim that a particular regressor is important (statistically significant) for explaining the outcome variable (y). Those who focus on p-values while ignoring the size of what is at stake are called p-hackers. When there...

A popular F test of Granger-causality relies on normally distributed errors of ordinary least squares (OLS) linear regressions. There is a long-standing need for a user-friendly algorithm replacing the OLS by kernel regressions, and the F test by a bootstrap. This paper introduces a version...

Volcker Rule suggests a break-up of 'too big to fail' financial institutions to prevent future costly bailouts and great recessions. We need to (i) regulate derivative trading to make it more transparent, (ii) fix conflicts of interest in ratings agencies, (iii) ban shadow-banking and...