Marital Status,Spousal Characteristics,and the Use of Preventive Care

In this article, we investigated the effects of marriage and spousal characteristics on the use of preventive care. We accounted for the endogeneity of marriage by combining propensity score estimation techniques with marriage transitions observed in longitudinal data. Results indicated that marriage increases the probability of dental check-ups and physical examinations for both sexes and mammograms and Pap smears for women. Next, we examined whether spousal characteristics affect the use of preventive care. Spousal education, income, health conditions, and preferences for risk and health care all affected use of preventive care in expected directions. Taken together, we conclude that marriage increases the use of preventive care; however, the net marital effect masks a heterogeneity that results from the characteristics of the spouse an individual marries.     

Uniform Convergence of Compactly Supported Wavelet Expansions of Gaussian Random Processes

New results on uniform convergence in probability for expansions of Gaussian random processes using compactly supported wavelets are given. The main result is valid for general classes of non stationary processes. An application of the obtained results to stationary processes is also presented. It is shown that the convergence rate of the expansions is exponential.     

Convergence Rate of Wavelet Expansions of Gaussian Random Processes

This article characterizes uniform convergence rate for general classes of wavelet expansions of stationary Gaussian random processes. The convergence in probability is considered.     

Robust estimation of AR coefficients under simultaneously influencing outliers and missing values

A family of robust estimators for coefficients of Gaussian AR(p) time series under simultaneously influencing distortions of two types: outliers and missing values, is proposed. The estimators are based on special properties of the Cauchy probability distribution; consistency and the asymptotic normality of these estimators are proven. An approximate solution of the problem of minimization of the asymptotic variance within the proposed family of estimators is found. Performance of the proposed estimators is illustrated for simulated time series and for real data sets.     

On drift parameter estimation in models with fractional Brownian motion

We consider a stochastic differential equation involving standard and fractional Brownian motion with unknown drift parameter to be estimated. We investigate the standard maximum likelihood estimate of the drift parameter, two non-standard estimates and three estimates for the sequential estimation. Model strong consistency and some other properties are proved. The linear model and Ornstein–Uhlenbeck model are studied in detail. As an auxiliary result, an asymptotic behaviour of the fractional derivative of the fractional Brownian motion is established.     

FINANCIAL CONSTRAINTS AND INNOVATION: WHY POOR COUNTRIES DON'T CATCH UP

This paper examines micro‐level channels through which financial development can affect such macroeconomic outcomes as level of income. Specifically, we investigate theoretically and empirically how financial constraints affect a firm's innovation activities. Theoretical predictions are tested using unique firm survey data, which provide direct measures for innovations and firm‐specific financial constraints, as well as information on shocks to firms' internal funds that serve as firm‐level instruments for financial constraints. We find unambiguous evidence that financial constraints restrain the ability of domestically owned firms to innovate and hence to catch up to the technological frontier.     

Construction of a criterion for testing hypothesis about covariance function of a stationary Gaussian stochastic process with unknown mean

In this paper, a new criterion is constructed for testing hypothesis about covariance function of Gaussian stationary stochastic process with an unknown mean. This criterion is based on the fact that we can estimate the deviation of covariance function from its estimator with a given accuracy and reliability in L_p metric.     

Probabilistic Assessment of the Failure Risk of the Europa Clipper Spacecraft due to Radiations

The Europa mission approved in 2019 is still in the development phase. It is designed to conduct a detailed reconnaissance of that moon of Jupiter as it could possibly support life as we know it. This article is based on a top-down approach (mission → system → subsystems → components) to model the probability of mission failure. The focus here is on the case where the (uncertain) radiation load exceeds the (uncertain) capacity of critical subsystems of the spacecraft. The model is an illustrative quantification of the uncertainties about (1) the complex external radiation environment in repeated exposures, (2) the effectiveness of the shielding in different zones of the spacecraft, and (3) the components’ capacities, by modeling all three as dynamic random variables. A simulation including a sensitivity analysis is used to obtain the failure probability of the whole mission in forty-five revolutions around Jupiter. This article illustrates how probabilistic risk analysis based on engineering models, test results and expert opinions can be used in the early stages of the design of space missions when uncertainties are large. It also describes the optimization of the spacecraft design, taking into account the decisionmakers’ risk attitude and the mission resource constraints.     

The Effects of the Informal Sector on Income of the Poor in Russia

This paper clarifies the social and economic effects of employment in the informal sector on the poor in Russia in recent years. The article describes the extent to which the figures for informal sector at large and unofficial employment in particular vary in different estimates and the effect they have on the average labor income of the poor. The major impact of the research consists of the development of a universal method for the estimation of the scales of labor income of the poor in the informal sector. Using the latest available data from Russian Federal State Statistics Service, this indicator is calculated for the poor and than compared with average wages in the formal sector and the subsistence minimum (official poverty line). The study concludes that the informal sector is a factor of social stability in a postsocialist transition economy, which, however, cannot alleviate poverty.     

Forecast Error Variance Decompositions with Local Projections

Abstract

We propose and study properties of an estimator of the forecast error variance decomposition in the local projections framework. We find for empirically relevant sample sizes that, after being bias-corrected with bootstrap, our estimator performs well in simulations. We also illustrate the workings of our estimator empirically for monetary policy and productivity shocks. KEYWORDS: Forecast error variance decomposition; Local projections.