the determinants and the selection of mexico us migrants using data from the mexican family life survey mxfls a panel of mexican individuals interviewed in 2002 and 2005 we analyze the characteristics of migrants from mexico to the us relative to non migrates and those who migrated and subsequently returned to mexico using pre and post migration earnings and their earnings in the us from the american community survey acs we characterize the selection of migrants on observable and non observable characteristics merging the data with us american community survey data we can also measure the expected earnings premium of migration to the us and the earnings premium for those that returned to mexico we find that migrants respond to the expected earnings premium to migration once we control for migration costs also the structure of the premium across skill groups generates negative selection on average and it can explain selection on observable and unobservables we also find that returnees are more positively selected over skills than migrants to the us initial poverty old age and family ties are strong deterrents of migration to the us once we account for the skill specific migration premium we also fi nd as trong under representation of college educated among migrants to the us possibly a consequence of the fact that undocumented migration is not an attractive option for those individuals

model choice and value at risk performance broad agreement exists among both the investment banking and regulatory communities that the use of internal risk management models is an efficient means for calculating capital risk requirements the determination of model parameters laid down by the basle committee on banking supervision as necessary for estimating and evaluating the capital adequacies however has received little academic scrutiny we investigate a number of issues of statistical modeling in the context of determining market based capital risk requirements we highlight several potentially serious pitfalls in commonly applied methodologies and conclude that simple methods for calculating value at risk often provide superior performance to complex procedures our results thus have important implications for risk managers and market regulators

value at risk estimation with the optimal dynamic biofuel portfolio abstract in the past petroleum companies only paid attention to hedging the variation in the crude oil price and volatility however they have now expanded their analysis to encompass renewable sources such as corn and soybeans under the current low carbon biofuel obligations this paper employs garch 1 1 and arji models to estimate the one day ahead value at risk var of the optimal dynamic biofuel portfolio which consists of crude oil corn and soybeans the optimal blended standard is subject to the dual limitations of minimum production costs and the lowest biofuel using requirements our empirical findings confirm that the arji model is more suitable than the garch 1 1 model and further captures the discontinuous jump behavior from the in the sample data the results of out of sample forecasts also are represented that our models play important roles in var estimation and risk management for biofuel portfolio we therefore suggest that the petroleum companies should simultaneously pay attention to jump risk in hedging material costs in the prices of energy related crops

oil prices brownian motion or mean reversion a study using a one year ahead density forecast criterion abstract for oil related investment appraisal an accurate description of the evolving uncertainty in the oil price is essential for example when using real option theory to value an investment a density function for the future price of oil is central to the option valuation the literature on oil pricing offers two views the arbitrage pricing theory literature for oil suggests geometric brownian motion and mean reversion models empirically driven literature suggests arma garch models in addition to reflecting the volatility of the market the density function of future prices should also incorporate the uncertainty due to price jumps a common occurrence in the oil market in this study the accuracy of density forecasts for up to a year ahead is the major criterion for a comparison of a range of models of oil price behaviour both those proposed in the literature and following from data analysis the kullbach leibler information criterion is used to measure the accuracy of density forecasts using two crude oil price series brent and west texas intermediate wti representing the us market we demonstrate that accurate density forecasts are achievable for up to nearly two years ahead using a mixture of two gaussians innovation processes with garch and no mean reversion

evaluating interval forecasts a complete theory for evaluating interval forecasts has not been worked out to date most of the literature implicitly assumes homoskedastic errors even when this is clearly violated and proceed by merely testing for correct unconditional coverage consequently i set out to build a consistent framework for conditional interval forecast evaluation which is crucial when higher order moment dynamics are present the new methodology is demonstrated in an application to the exchange rate forecasting procedures advocated in risk management

bundling health insurance and microfinance in india there cannot be adverse selection if there is no demand most of the world s poor face large risks which affect their investment decisions and contribute to the perpetuation of poverty karlan et al 2013 in this context insurance products targeted at the poor are seen as having substantial promise as opportunities both to make profit and to improve efficiency and social welfare the marketing of insurance products to the poor has faced two obstacles however first demand for insurance products is generally low cole et al 2013 second insurers have been worried about adverse selection and moral hazard with the latter concern leading insurers to offer only basic products e g indexed weather insurance or catastrophic health insurance bundling insurance policies with other products such as microfinance loans has been seen as a promising solution to both the demand and the adverse selection problems see e g ilo 2013 under the theory that even those who derive little benefit from insurance would still want the bundled services microfinance institutions might either serve as an agent to a larger insurance company or offer the insurance policy themselves the hope is that bundling would create a large pool of non selected clients eliminating adverse selection and reducing administrative costs major health expenditures are a significant source of risk for the world s poor that is not well insured even by the informal insurance network that households typically call upon gertler and gruber 2002 fafchamps and lund 2003 many microfinance institutions have therefore experimented with bundling health insurance with their loans drawing evidence from the randomized introduction of a health insurance program bundled with a standard microfinance program we show that the basic presumption that bundling the two would lead to a large client base is wrong we find that a large fraction of borrowers 16 percentage points were actually willing to give up microfinance to avoid purchasing health insurance and that the majority of those clients ended up losing access to microfinance altogether the observed client dropout while discouraging for the microfinance institution and the insurer provides an opportunity to observe whether the original concerns of adverse selection are actually a main barrier to providing health insurance we find that the answer to this question is an emphatic no there is no evidence that clients dropping out to avoid purchasing insurance are systematically different from those who remain clients in terms of their propensity to have insurable health care expenses including covered maternity expenses that are most easily predictable it seems that insurers policy makers and academics are one step ahead of insurance clients the central issue seems not to be that only those who need health insurance would be willing to sign up but that even those who would need it are not willing to sign up for it potentially at the cost of losing a valuable resource

migration experience and earnings in the mexican labor market we present a theoretical and empirical analysis of the relationship between u s migration experience and earnings in the mexican labor market we use our model to analyze the effects of self selection and endogeneity on ols estimates of the return to migration experience in the mexican labor market under plausible assumptions ols estimates provide a lower bound on the true average return to migration experience among return migrants using mexican migration project mmp data we find a return to migration experience of about 2 2 percent per year our estimates are robust to the inclusion of proxies for unobserved skill a comparison with patterns in the 1995 mexican population and dwelling count suggests that our results are robust across data sets and are driven by a relationship between migration experience and wages not hours worked we also explore the plausibility of multiple mechanisms that could explain this relationship we find the most evidence for the theory that individuals are acquiring occupation specific work experience in the united states the return to a year of occupation specific migration experience is estimated to be as high as 8 7 percent for some occupations

return migration and violence abstract there is reason to suspect that return migrants can reduce social violence in migrant prone regions of the world taking into account that recent research shows positive effects of return migration we consider that returners may reduce violence by contributing to social renewal and economic growth in their home communities we estimate the direct effects of return migration in the context of mexico a traditionally migrant country that has suffered record levels of violence in the past decade using data on homicide rates from 2456 municipalities for the 2011 2013 period and an instrumental variable bivariate tobit maximum likelihood approach we find that higher rates of return migration lead to a decline in local homicide rates we also show with a censored quantile instrumental variable cqiv model that municipalities in the bottom quartile of the homicide rate distribution benefit the most from return migration our work has important implications for crime reduction policies in developing countries and specifically in mexico where social violence has wreaked havoc on society in recent years

modeling and forecasting extreme commodity prices a markov switching based extreme value model abstract we propose a markov switching multifractal peaks over threshold msm pot model to capture the dynamic behavior of the random occurrences of extreme events exceeding a high threshold in time series of returns this approach allows introducing changes of regimes in the conditional mean function of the inter exceedance times i e the time between two consecutive extreme events in order to admit the presence of short and long term memory patterns further through its multifractal structure the msm pot approach is able to capture the typical stylized facts of extreme events observed in financial time series such as temporal clustering of the size of exceedances and temporal behavior of tail thickness we compare the performance of the msm pot model with competing self exciting models and a garch evt approach in an in and out of sample var forecasting exercise based on the extreme returns of six daily commodity futures prices i e brent and wti crude oil cocoa cotton copper and gold empirical results suggest that the var estimates generated by the msm pot model for the returns analyzed produce the most accurate forecasts

leverage effects and stochastic volatility in spot oil returns a bayesian approach with var and cvar applications abstract crude oil markets have been quite volatile and risky in the past few decades due to the large fluctuations of oil prices we contribute to the current debate by testing for the existence of the leverage effect when considering daily spot returns in the wti and brent crude oil markets and by studying the direct impact of the leverage effect on measures of risk such as var and cvar more specifically we model spot crude oil returns using stochastic volatility sv models with various distributions of the errors we find that the introduction of the leverage effect in the traditional sv model with normally distributed errors is capable of adequately estimating risk for speculative oil suppliers in both the wti and brent markets our results also show that financial regulators model choice both on the supply and on the demand side would not be affected by the introduction of leverage focusing instead on firm s internal risk management our results show that the introduction of leverage would be useful for firms who are on the demand side for oil who use var for risk management and who are particularly worried about the magnitude of the losses exceeding var while wanting to minimize the opportunity cost of capital using the same logic firms who are on the supply side would be better off not considering the leverage effect

investment and interruption effects of the us experience on the earnings of return migrants in mexico migration is widely viewed as an investment in human capital however due to the imperfect transferability of skills and knowledge across countries migration trips are also career interruptions especially for return migrants who may meanwhile experience depreciation of home country specific skills this article demonstrates that migration experience increases return migrants earnings in the home country on the condition that the migration stay is sufficiently long and mostly uninterrupted employing the revised human capital earnings function the empirical study shows that only a barely interrupted us experience longer than five years regardless of the legal status of the migration trips predicts higher earnings of male return migrants in mexico than comparable non migrants robust findings emerge controlling for unobserved individual acteristics or using instrumental variables to deal with the self selection and endogeneity short migration stays in the us and frequent traveling provide

value at risk estimation of energy commodities a long memory garch evt approach abstract in this paper we evaluate value at risk var and expected shortfall es for crude oil and gasoline market we adopt three long memory models including figarch hygarch and fiaparch to forecast energy commodity volatility by capturing some volatility stylized fact such as long range memory heteroscedasticity asymmetry and fat tails then we consider extreme value theory which concentrates on the tail distribution rather than the entire distribution evt is considered as a potential framework for the separate treatment of tails of distributions which allows for asymmetry our results show that the fiaparch model with extreme value theory performs better in predicting the one day ahead var using the fitted long memory garch model and a simulation approach to estimate var for horizons over than one day backtesting results show that our approach still performs for lower estimation frequencies overall our findings confirm that taking into account long range memory asymmetry and fat tails in the behavior of energy commodity prices returns combined with filtering process such as evt are important in improving risk management assessments and hedging strategies in the high volatile energy market

return migration wage differentials and the optimal migration duration in simple static models migration increases with the wage differential between host and home country in a dynamic framework and if migrations are temporary the size of the migrant population in the host country depends also on the migration duration this paper analyses optimal migration durations in a model which rationalises the decision of the migrant to return to his home country despite persistently higher wages in the host country the analysis shows that if migrations are temporary the optimal migration duration may decrease if the wage differential grows larger using micro data for germany the second part of the paper provides empirical evidence which is compatible with this hypothesis

network effects and the dynamics of migration and inequality theory and evidence from mexico international migration is costly and initially only the middle class of the wealth distribution may have both the means and incentives to migrate which can increase inequality in the sending community however the migration networks formed lower the costs for future migrants which can in turn lower inequality this paper shows both theoretically and empirically that wealth has a nonlinear effect on migration and then examines the empirical evidence for an inverse u shaped relationship between emigration and inequality in rural sending communities in mexico after instrumenting we find that the overall impact of migration is to reduce inequality across communities with relatively high levels of past migration we also find some suggestive evidence for an inverse u shaped relationship among communities with a wider range of migration experiences

homesickness and repeated migration this paper presents a dynamic structural model of migration that is designed to help explain the migration behaviour of undocumented mexican immigrants in the us its key feature which i call ho

migration networks and microenterprises in mexico are migration networks associated with lower capital costs or the alleviation of capital constraints we examine these questions with data measuring access to remittance flows among small scale entrepreneurs in mexico using a survey of more than 6000 self employed workers and small firm owners located in 44 urban areas of mexico we estimate the impact of attachment to migration networks on the level of capital investment the capital output ratio sales and profits of microenterprises the impact is identified from the geographic pattern of migration from mexico driven by the completion of rail lines in the early 1900s for the full sample of firms we find that migration is associated with higher investment levels and higher profits but not higher sales the strongest effects on investment are in the categories of automobiles tools and inventories when the sample is limited to firms in high capital sectors investment sales and profits all increase with attachment to the migration networks suggesting that attachment to the migration network alleviates capital constraints in those sectors

the impact of liquidity on portfolio value at risk forecasts abstracthistorical crisis events have highlighted the insufficiency of value at risk var as a measure of market risk because such metric does not take liquidity into account unlike previous stud

estimating oil price value at risk using the historical simulation approach abstract in this paper we propose using value at risk var for oil price risk quantification var provides an estimation for the maximum oil price change associated with a likelihood level and can be used for designing risk management strategies we analyse three var calculation methods the historical simulation standard approach the historical simulation with arma forecasts hsaf approach developed in this paper and the variance covariance method based on autoregressive conditional heteroskedasticity models forecasts the results obtained indicate that hsaf methodology provides a flexible var quantification which fits the continuous oil price movements well and provides an efficient risk quantification

return migration human capital accumulation and the brain drain in this paper we present a model that explains migrations as decisions that respond to where human capital can be acquired more efficiently and where the return to human capital is highest the basic framework is a dynamic roy model in which a worker possesses two distinct skills that can be augmented by learning by doing there are different implicit price in different countries and different rates of skill accumulation our analysis contributes to the literature on the selection of immigrants and return migrants by offering a richer framework that may help to accommodate selections of emigrants and return migrants that are not immediately compatible with the one dimensional skill model our analysis has also implications for the debate on brain drain and brain gain in the two skills model presented here return migration can lead to a mitigation of the brain drain or even the creation of a brain gain where those who return bring the home country augmented local skills

the economics of temporary migrations many migrations are temporary a fact that has often been ignored in the economic literature on migration such omission may be serious in that expected migration temporariness can impart a distinct dynamic element to immigrants economic behavior generating possible consequences for nonmigrants in both home and host countries in this paper we provide a thorough examination of the various aspects of temporary migrations that matter for the analysis of economic phenomena we demonstrate the extent of temporary migrations in population movements we show how temporariness can affect the various economic choices and how better data have improved both the measurement of nonpermanent migrations and the analyses of various aspects of migrant behavior we propose a general theoretical framework for modeling temporary migration decisions based on which we outline the various motives for temporariness while simultaneously reviewing related literature and available data sources we discuss the possible consequences of migration temporariness for nonmigrants in both home and host countries jel f22 f24 j11 j61 k37 o15

self selection and the earnings of immigrants this paper analyzes the way in which the earnings of the immigrant population may be expected to differ from the earnings of the native population because of the endogeneity of the decision to migrate the empirical study shows that differences in the u s earnings of immigrants with the same measured skills but from different home countries are attributable to variations in political and economic conditions in the countries of origin at the time of migration excerpt

estimation of value at risk for energy commodities via fat tailed garch models the choice of an appropriate distribution for return innovations is important in var applications owing to its ability to directly affect the estimation quality of the required quantiles this study investigates the influence of fat tailed innovation process on the performance of one day ahead var estimates using three garch models garch n garch t and garch ht daily spot prices of five energy commodities wti crude oil brent crude oil heating oil 2 propane and new york harbor conventional gasoline regular are used to compare the accuracy and efficiency of the var models empirical results suggest that for asset returns that exhibit leptokurtic and fat tailed features the var estimates generated by the garch ht models have good accuracy at both low and high confidence levels additionally mrsb indicates that the garch ht model is more efficient than alternatives for most cases at high confidence levels these findings suggest that the heavy tailed distribution is more suitable for energy commodities particularly var calculation

coming out of the shadows learning about legal status and wages from the legalized population the 1986 immigration reform and control act irca granted amnesty to approximately 1 7 million long term unauthorized workers in an effort to bring them out of the shadows and improve their labor market opportunities an analysis of wages using panel data for a sample of legalized men provides evidence that wage determinants are structurally different after amnesty for them but not for the comparison group as measured during the same time periods the wage penalty for being unauthorized is estimated to range from 14 to 24 the wage benefit of legalization under irca was approximately 6

forecasting the var of crude oil market do alternative distributions help abstract accurate modeling of the empirical distribution of crude oil market returns is extremely important in estimating risk measures in addition to several commonly used distributions alternative distributions are explored in this study some of which account for the asymmetry and heavy tails simultaneously found in distributions and contain more tail parameters to separately depict the right and left tails when forecasting the value at risk var of crude oil markets during highly volatile periods seven backtests are also conducted to compare the var forecasting accuracy among different distributions the empirical results indicate that a highly volatile environment challenges the commonly used distributions and the four risk models based on commonly used distributions are rejected about 27 to 38 of the time the alternative distributions i e skewed general error distributions sged generalized hyperbolic skewed student t distributions ghst and generalized asymmetric student t gast distributions generally produce more accurate var measurement and gast gives the best measurement accuracy the empirical results imply that risk managers or policymakers should further consider more flexible distributions such as sged ghst or gast in particular when quantifying or managing the risk in turbulent market times

residual shape risk on natural gas market with mixed jump diffusion price dynamics abstract this paper introduces residual shape risk as a new subclass of energy commodity risk residual shape risk is caused by insufficient liquidity of energy forward market when retail energy supplier has to hedge his short sales by a non flexible standard baseload product available on wholesale market because of this inflexibility energy supplier is left with residual unhedged position which has to be closed at spot market the residual shape risk is defined as the difference between spot and forward prices weighted by residual unhedged position whose size depends on the shape of customers portfolio of a given retail energy supplier we evaluated residual shape risk over the years 2014 2018 with a real portfolio of a leading natural gas retail supplier in the czech republic the size of residual shape risk in our example corresponds approximately to 1 percent of the profit margin of the natural gas retail supplier

market risk in commodity markets a var approach we put forward value at risk models relevant for commodity traders who have long and short trading positions in commodity markets in a 5 year out of sample study on aluminium copper nickel brent crude oil and wti crude oil daily cash prices and cocoa nearby futures contracts we assess the performance of the riskmetrics skewed student aparch and skewed student arch models while the skewed student aparch model performs best in all cases the skewed student arch model delivers good results and its estimation does not require non linear optimization procedures as such this new model could be relatively easily integrated in a spreadsheet like environment and used by market practitioners

modelling general dependence between commodity forward curves abstract this study proposes a novel framework for the joint modelling of commodity forward curves its key contribution is twofold first we introduce a family of dynamic conditional correlation models based on hierarchical archimedean copulae hac dcc which are flexible but parsimonious instruments that capture a wide range of dynamic dependencies second we apply these models in the context of commodity forward curves as part of the framework an extensive value at risk analysis shows that certain hac dcc models consistently outperform other introduced benchmarks in terms of the preciseness of their out of sample distribution forecasts of the returns of various commodity futures portfolios this shows that the proposed modelling framework as one of its possible applications can be a useful and convenient risk management tool

how relevant is volatility forecasting for financial risk management it depends if volatility fluctuates in a forecastable way volatility forecasts are useful for risk management hence the interest in volatility forecastability in the risk management literature volatility forecastability however varies with horizon and different horizons are relevant in different applications moreover existing assessments of volatility forecastability are plagued by the fact that they are joint assessments of volatility forecastability and an assumed model and the results can vary not only with the horizon but also with the assumed model to address this problem we develop a model free procedure for assessing volatility forecastability across horizons perhaps surprisingly we find that volatility forecastability decays quickly with horizon volatility forecastability although clearly of relevance for risk management at the short horizons relevant for say trading desk management may be much less important at longer horizons

value at risk for long and short trading positions in this paper we model value at risk var for daily stock index returns using a collection of parametric models of the arch family based on the skewed student distribution we show that models that rely on a symmetric density distribution for the error term underperform with respect to skewed density models when the left and right tails of the distribution of returns must be modelled thus var for traders having both long and short positions is not adequately modelled using usual normal or student distributions we suggest using an aparch model based on the skewed student distribution to fully take into account the fat left and right tails of the returns distribution this allows for an adequate modelling of large returns defined on long and short trading positions the performances of all models are assessed on daily data for the cac40 dax nasdaq nikkei and smi stock indexes we also compute the expected short fall and the average multiple of tail event to risk measure for the new model

international migration self selection and the distribution of wages evidence from mexico and the united states we use the 1990 and 2000 mexican and u s population censuses to test borjas s negative selection hypothesis that the less skilled are those most likely to migrate from countries with high skill premia earnings inequality to countries with low skill premia earnings inequality we find that mexican immigrants in the united states are more educated than nonmigrants in mexico and were mexican immigrants to be paid according to current skill prices in mexico they would be concentrated in the middle of mexico s wage distribution these results are inconsistent with the negative selection hypothesis and instead suggest that there is intermediate selection of immigrants from mexico