Financial Inclusion Through Public Works Program: Does Gender-Based Violence Make a Difference?

The study investigates the impact of gender-related violence on financial inclusion. Exploiting the staggered rollout of a major public works program across Indian districts, we find evidence that households in states with gender-related violence are less likely to own a bank account, notwithstanding the fact that districts in these states were early implementers of the public works program. These findings are however, different after the government launched a massive program to promote universal financial inclusion. To be more specific, we find evidence of an increase in account ownership consistent during this period by over 100 percentage points, although the use of bank account by working women declines significantly. These findings of increased access are consistent with the bargaining theory, which suggests by gaining greater resources, women also gain more power. However, low use of accounts highlights the theory of male backlash as a response to undermined economic role at home. Overall, these results suggest that any attempt at ensuring universal financial inclusion needs to adequately take on board the aspect of gender-related violence, which can be the outcome of not only economic, but also social and cultural factors.     

A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms

This article investigates farm-level efficiency of U.S. dairy farmers by estimating their technical and allocative efficiency. Technical inefficiency is assumed to be composed of a deterministic component that is a function of some farm-specific characteristics and a random component. By doing this we extend the stochastic frontier methodology in which determinants of technicial inefficiency are explicitly introduced in the model. Given the inputs, variations in efficiency of farms are then explained by both deterministic and random components of technical inefficiency. The empirical results indicate that (a) levels of education of the farmer are important factors determining technical inefficiency and (b) large farms are more efficient (technically) than small and medium-sized farms. Both technical and allocative inefficiency are found to decrease with increase in the level of education of the farmer.     

The behrens‐fisher problem revisited: A bayes‐frequentist synthesis

The Behrens‐Fisher problem concerns the inference for the difference between the means of two normal populations whose ratio of variances is unknown. In this situation, Fisher's fiducial interval differs markedly from the Neyman‐Pearson confidence interval. A prior proposed by Jeffreys leads to a credible interval that is equivalent to Fisher's solution but it carries a different interpretation. The authors propose an alternative prior leading to a credible interval whose asymptotic coverage probability matches the frequentist coverage probability more accurately than the interval of Jeffreys. Their simulation results indicate excellent matching even in small samples.     

Adjustment costs in labour markets and the distributional effects of trade liberalization: Analytics and calculations for Vietnam

This paper explores the implications of different labour market adjustment formulations for the analysis of trade liberalization across different sectors and households in the Vietnamese economy using computable general equilibrium (CGE) models. The model is calibrated to a model admissible Vietnamese data set for 1997.We use five different adjustment cost treatments in analyzing the effects of trade liberalization in Vietnam. We compare simulation results from each and show how different treatments can significantly affect the distributional impacts of policy reforms, such as the trade liberalization. First, labour is treated as fully mobile across all sectors in the economy. Second, the sectors of economy are broken down into the two blocks of agricultural and industrial-service sectors and labour markets are treated as segmented by sector block. No mobility of labour between blocks is allowed while labour within each sector block remains fully mobile. The third is the same as the second, but movement within each agricultural and industrial-service sector block involves transactions costs. In the fourth, mobility of workers from the agricultural to industrial-service sectors and vice versa is possible with transactions costs. Finally, we calibrate the model with unemployment but no adjustment costs for labour reallocation to explore how model results differ in terms of adjustments in the labour market and welfare effects.Our results indicate significant differences in the impacts from trade liberalization across these cases. The redistributional impact of trade liberalization is sharper against poor rural households with segmented labour markets and with transactions costs, while aggregate efficiency gains are similar to no adjustment cost analyses. The conclusion is the choice of model structure for labour markets is crucially important for the perceived distributional impacts of trade liberalization.     

Study of incompatibility or near compatibility of bivariate discrete conditional probability distributions through divergence measures

Consider a two-dimensional discrete random variable (X, Y) with possible values 1, 2, …, I for X and 1, 2, …, J for Y. For specifying the distribution of (X, Y), suppose both conditional distributions, of X given Y and of Y given X, are provided. Under this setting, we present here different ways of measuring discrepancy between incompatible conditional distributions in the finite discrete case. In the process, we also suggest different ways of defining the most nearly compatible distributions in incompatible cases. Many new divergence measures are discussed along with those that are already known for determining the most nearly compatible joint distribution P. Finally, a comparative study is carried out between all these divergence measures as some examples.     

Kalman filter-based modelling and forecasting of stochastic volatility with threshold

We propose a parametric nonlinear time-series model, namely the Autoregressive-Stochastic volatility with threshold (AR-SVT) model with mean equation for forecasting level and volatility. Methodology for estimation of parameters of this model is developed by first obtaining recursive Kalman filter time-update equation and then employing the unrestricted quasi-maximum likelihood method. Furthermore, optimal one-step and two-step-ahead out-of-sample forecasts formulae along with forecast error variances are derived analytically by recursive use of conditional expectation and variance. As an illustration, volatile all-India monthly spices export during the period January 2006 to January 2012 is considered. Entire data analysis is carried out using EViews and matrix laboratory (MATLAB) software packages. The AR-SVT model is fitted and interval forecasts for 10 hold-out data points are obtained. Superiority of this model for describing and forecasting over other competing models for volatility, namely AR-Generalized autoregressive conditional heteroscedastic, AR-Exponential GARCH, AR-Threshold GARCH, and AR-Stochastic volatility models is shown for the data under consideration. Finally, for the AR-SVT model, optimal out-of-sample forecasts along with forecasts of one-step-ahead variances are obtained.     

Identification of confounded design and its interactions

Kane has discussed a simple method for identifying the confounded interactions from 2ⁿ factorial experiments when a replication consists of (1) two blocks and (2) more than two blocks. It should be noted that Kane's method holds only for (1) regular design and (2) when one interaction is confounded. In the present investigation, we proposed a new way of identifying the confounded designs and the confounded interactions in 2ⁿ factorial experiments. Furthermore, the same method is extended to 3ⁿ and Sⁿ factorial experiments.     

Efficiency balanced designs through reinforcement

In this investigation, general efficiency balanced (GEB) and efficiency balanced (EB) designs with (v + t) treatments, using (i) balanced incomplete block (BIB), (ii) symmetrical BIB, (iii) f -resolvable BIB, (iv) group divisible (GD) and (v) resolvable GD designs have been constructed with smaller number of replications and block sizes.     

Bayesian analysis for a stress-strength system under noninformative priors

Noninformative priors are used for estimating the reliability of a stress-strength system. Several reference priors (cf. Berger and Bernardo 1989, 1992) are derived. A class of priors is found by matching the coverage probabilities of one-sided Bayesian credible intervals with the corresponding frequentist coverage probabilities. It turns out that none of the reference priors is a matching prior. Sufficient conditions for propriety of posteriors under reference priors and matching priors are provided. A simple matching prior is compared with three reference priors when sample sizes are small. The study shows that the matching prior performs better than Jeffreys's prior and reference priors in meeting the target coverage probabilities.