Linking the statistic and the machine learning literature, we provide new general results on the convergence of stochastic approximation schemes and inexact Newton methods. Building on these results, we put forward a new optimization scheme that we call generalized inexact Newton method (GINM)....

Linking the statistic and the machine learning literature, we provide new general results on the convergence of stochastic approximation schemes and inexact Newton methods. Building on these results, we put forward a new optimization scheme that we call generalized inexact Newton method (GINM)....

Accurate poverty measurement relies on household consumption data, but such data are often inadequate, outdated or display inconsistencies over time in poorer countries. To address these data challenges, we employ survey-to-survey imputation to produce estimates for several poverty indicators...

This article intends to expose a process for the valuation of shares of the companies of the banking sector through business financial multiples, based on various statistical techniques such as Monte Carlo simulations and Bayesian models of continuous valuation of the relative indicators over...

We study cluster-robust inference for binary response models. Inference based on the most commonly-used cluster-robust variance matrix estimator (CRVE) can be very unreliable. We study several alternatives. Conceptually the simplest of these, but also the most computationally demanding, involves...

We study the performance of two analytical methods and one simulation method for computing in-sample confidence bounds for time-varying parameters. These in-sample bounds are designed to reflect parameter uncertainty in the associated filter. They are applicable to the complete class of...

We study cluster-robust inference for binary response models. Inference based on the most commonly-used cluster-robust variance matrix estimator (CRVE) can be very unreliable. We study several alternatives. Conceptually the simplest of these, but also the most computationally demanding, involves...

Accurate poverty measurement relies on household consumption data, but such data are often inadequate, outdated or display inconsistencies over time in poorer countries. To address these data challenges, we employ survey-to-survey imputation to produce estimates for several poverty indicators...

Persistence is the speed with which a time series returns to its mean after a shock. Although several measures of persistence have been proposed in the literature, when they are empirically applied, the different measures indicate incompatible messages, as they differ both in the level and the...

Biodiversity loss and environmental degradation can hit economies through multiple channels. The combined macroeconomic consequences can impact sovereign creditworthiness. Yet, the methodologies published and applied by leading credit rating agencies (CRAs) do not explicitly incorporate...