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Hypothesis tests for dominance in income distributions has received considerable attention in recent literature. See, for example, Barrett and Donald (2003a, b), Davidson and Duclos (2000) and references therein. Such tests are useful for assessing progress towards eliminating poverty and for evaluating the effectiveness of various policy initiatives directed towards welfare improvement. To date the focus in the literature has been on sampling theory tests. Such tests can be set up in various ways, with dominance as the null or alternative hypothesis, and with dominance in either direction (X dominates Y or Y dominates X). The result of a test is expressed as rejection of, or failure to reject, a null hypothesis. In this paper, we develop and apply Bayesian methods of inference to problems of Lorenz and stochastic dominance. The result from a comparison of two income distributions is reported in terms of the posterior probabilities for each of the three possible outcomes: (a) X dominates Y, (b) Y dominates X, and (c) neither X nor Y is dominant. Reporting results about uncertain outcomes in terms of probabilities has the advantage of being more informative than a simple reject/do-not-reject outcome. Whether a probability is sufficiently high or low for a policy maker to take a particular action is then a decision for that policy maker.

The methodology is applied to data for Canada from the Family Expenditure Survey for the years 1978 and 1986. We assess the likelihood of dominance from one time period to the next. Two alternative assumptions are made about the income distributions – Dagum and Singh-Maddala – and in each case the posterior probability of dominance is given by the proportion of times a relevant parameter inequality is satisfied by the posterior observations generated by Markov chain Monte Carlo.

We use stochastic dominance to test whether investors should prefer riskier securities as the investment horizon lengthens. Simulated return distributions for stocks, bonds, and U.S. Treasury bills are generated for holding periods of one to 20 years and stochastic dominance tests are run to establish preferences among the alternative portfolios. With independent returns, we find no evidence that high-risk securities (stocks) dominate low-risk securities (bonds) as the investment horizon lengthens. Under the assumption that security returns are correlated across time, we find that common stocks dominate corporate bonds and U.S. Treasury bills for sufficiently long investment horizons.

In an evaluation of a job training program, the causal effects of the program on wages are often of more interest to economists than the program's effects on employment or on income. The reason is that the effects on wages reflect the increase in human capital due to the training program, whereas the effects on total earnings or income may be simply reflecting the increased likelihood of employment without any effect on wage rates. Estimating the effects of training programs on wages is complicated by the fact that, even in a randomized experiment, wages are truncated by nonemployment, i.e., are only observed and well-defined for individuals who are employed. We present a principal stratification approach applied to a randomized social experiment that classifies participants into four latent groups according to whether they would be employed or not under treatment and control, and argue that the average treatment effect on wages is only clearly defined for those who would be employed whether they were trained or not. We summarize large sample bounds for this average treatment effect, and propose and derive a Bayesian analysis and the associated Bayesian Markov Chain Monte Carlo computational algorithm. Moreover, we illustrate the application of new code checking tools to our Bayesian analysis to detect possible coding errors. Finally, we demonstrate our Bayesian analysis using simulated data.

This paper deals with poverty decompositions into subgroups defined with respect to intervals of income and the robustness of comparisons of the absolute contribution of such groups to poverty. For instance, world poverty estimates by the World Bank often distinguish between the extreme poor whose incomes are lower than $1.25 a day (in PPP terms) and the other poor with incomes between $1.25 and $2.5 a day. Existing dominance conditions can tell whether overall poverty and extreme poverty have declined in a robust manner when comparing countries at two points of time, but they cannot say anything for the contribution of the non-extreme poor to overall poverty. In the present paper we propose stochastic generalized dominance criteria to perform robust poverty ordering when the focus is placed on some interval of the poverty domain. Using generated data based on grouped data from World Bank’s PovcalNet tool, the paper finally investigates whether the robust decline of extreme poverty around the world during the last decades was also accompanied by a decline of the contribution of non-extreme poverty.

This study analyzes the effect of ambiguity aversion on precautionary effort under a two period model when background risk like income risk is added to loss. Precautionary effort only affects the probability of loss occurrence. The sufficient conditions under which a risk averse and ambiguity averse individual makes more effort than a risk averse and ambiguity neutral one are as follows. First, the distribution of background risk changes in type of first order stochastic dominance. Second, the distribution of background risk changes in type of second order stochastic dominance and the utility function shows prudence. In both cases, AAA (absolute ambiguity aversion) should not increase. That is, AAA denotes DAAA (Decreasing Absolute Ambiguity Aversion) or CAAA (Constant Absolute Ambiguity Aversion). The effect of AAA is not observed in the existing literatures which assume a one-period model. In a one period model, the effect of AAA on precautionary effort of a long term may have ignored. Lastly, precautionary effort increases if and only if AAA is not increasing in cases when the background risk follows binary distribution or an individual is risk neutral and ambiguity averse.

This study uses stochastic dominance (SD) theory to examine whether the traditional festival, such as the Spring Festival (often in February), affects the patterns of monthly anomaly for the Taiwan Stock Exchange (TWSE). The paper aims to discuss these issues.

The authors employ a new bootstrap-based test due to Linton, Maasoumi and Whang (hereafter LMW). The LMW test is well suited for financial time series data, such as monthly returns of various portfolios in this study, because it allows for general dependence among the prospects (distributions) and does not require the observations to be identically and independently distributed.

The particular findings of this study are that the February effect and the February-size effect indeed exist in the TWSE. Furthermore, allowing part of investors' assets is invested in the risky asset and the remaining part in a risk-free asset, first finding for monthly anomaly in the extant literature, is useful in distinguishing the performance among various size-month portfolios.

Instead of tax-loss and window dressing hypothesis, the Spring Festival money movement hypothesis can be used to well explain the findings.

This paper aims to compare two groups of stocks to analyze the efficiency of an ethical portfolio in comparison with a conventional portfolio.

Efficiency test by second-order stochastic dominance (SSD) approach is applied on two groups, which consist of 12 stocks. Ethical portfolio is chosen from the stocks complying with the participation banking rules. Conventional portfolio is selected from Borsa Istanbul (BIST) with choosing the corresponding stocks for each ethical stock according to the sector and market capitalization. All the stocks of both groups are pairwise SSD compared.

Both groups of 12 stocks are inefficient portfolios; however, a group of 7 stocks constitute an efficient ethical portfolio with the total weight of 50.82 per cent among the set of 12 ethical stocks. On the other hand, a group of 6 stocks constitute an efficient conventional portfolio, with the total weight of 45.16 per cent among the set of 12 conventional stocks. By pairwise SSD comparison of corresponding stocks from both groups, despite none of the conventional stocks dominate ethical stocks, four ethical stocks dominated the conventional ones.

Back-testing and comparison with benchmark BIST 100 Index have been done for the selected portfolios. According to back-testing results, groups of SSD efficient stocks outperformed the groups, from which they were selected. Furthermore, both SSD efficient portfolios have higher returns than benchmark index, BIST 100.

The purpose of this paper is to empirically investigate the Saturday effect in three emerging stock markets (Bahrain, Kuwait, and Saudi Arabia) by taking into consideration the thin trading that is normal in such capital markets.

The paper applies the stochastic dominance (SD) approach, which is not distribution‐dependent and can shed light on the utility and wealth implications of portfolio preferences by exploiting information in higher order moments, to investigate empirically the existence of the Saturday effect in the three Gulf stock markets.

The findings indicate that the Saturday effect does not manifest itself in the three Gulf stock markets and that the SD results show that the Saturday effect in these markets is not present when raw data are corrected for thin and infrequent trading.

This paper is believed to be the first to use SD approach to examine the Saturday effect.

Dominance techniques are used to analyze and rank inequality, welfare, and poverty across regions in Thailand in the 1990s. Inference-based dominance methods are applied to consumption expenditure microdata from the Household Socio-Economic Surveys (SES) of 1992, 1994, 1996, 1998 and 2000. Attention is focused on the period immediately before and after the economic contraction of 1996–1997. Lorenz dominance is employed to assess inequality, while first-order Engel food share dominance is applied to rank welfare across time and among regions. Poverty is evaluated by comparing truncated food-share quantile functions. The evidence reveals that the economic crisis in 1997 seems to affect inequality in Bangkok (the richest region) more than the Northeast (the poorest region), and most dramatic changes occur in the North and South. Welfare in Bangkok is unambiguously higher than in other regions before and after economic contraction. In fact, the great economic contraction changes the rankings of economic well-being and poverty only in the North, South, and Northeast.

The purpose of this paper is to determine the stochastic net present value (NPV) of a model smallholder poultry operation in Rwanda under production and market uncertainty.

A discounted cash flow calculator was used to determine the NPV of operator investments and operating cash flows, including time, materials and capital. Broiler production data, market prices and variable input costs were collected from 125 smallholder operations in the Musanze District, Rwanda. These data were combined with a historical price index tracking the inflation rate of Rwanda’s currency. Policies including overstocking, technical support repayment scheduling, selling broilers at a spot market price, using marketing contracts and selling poultry manure were compared using non-parametric paired comparisons and stochastic dominance.

Risk-neutral and risk-averse producers would prefer overstocking, delaying repayment of technical support services and selling manure to status quo operational policy. No differences were observed between the option to sell birds at spot market prices or through contracts.

This analysis demonstrates how individual managerial or an intervention in smallholder broiler production affects financial performance.

To mitigate risk associated with this novel enterprise, producers should consider overstocking birds. If local markets for manure were developed, the risks faced by new or beginning poultry operators could be mitigated.

A stochastic, discounted cash flow model calculator was used to determine the NPV and discounted payback period of operator investments and operating cash flows, including time, materials and capital.