charity care risk pooling and the decline in private health insurance over the past several decades health care costs have increased substantially and the share of the population with insurance coverage has decreased relative to gdp medical care today accounts for 75 percent more of the economy than it did in 1980 at the same time the share of the non elderly population that is uninsured has increased by roughly 4 percentage points since 1987 to what extent is the increase in the cost of health insurance responsible for the decline in coverage individuals will purchase coverage if the utility of being insured exceeds that of being uninsured textbook economic theory suggests that rising medical expenditures ought to increase the utility of coverage because insurance mitigates risk if the variability of spending rises as medical care costs increase insurance becomes more valuable charles phelps 1997 the rising demand for pharmaceutical coverage following the rise in spending on pharmaceuticals is consistent with this model in the textbook model rising costs would be associated with falling coverage only if the cost increases were driven by increased administrative loads empirically though most medical spending is a result of increased quantities of care received owing to technological changes in medicine not greater administrative burden cutler and mark mcclellan 2001 there are two extensions to the textbook model that can help explain the inverse relationship between premiums and insurance coverage the first is the hypothesis that the value of new services is not sufficiently high to justify their costs and thus some people rationally decline coverage when costs increase of course if consumers had the option they would exclude unvalued care from the insurance policy but determining which care is valuable and which is not may be difficult and contracting imperfections may make it difficult for individuals to purchase a plan that limits access to particular services one type of unvalued care is traditional moral hazard services are provided because of insurance but are worth less than they cost cutler 2004 shows that increased medical spending overall has bought care that is more than worth its value but that does not imply that the differential growth of service use in some areas discussants amitabh chandra dartmouth college ellen meara harvard medical school helen levy university of chicago darius lakdawalla rand corporation

best practices in demand forecasting tests of universalistic contingency and configurational theories abstract the paper focuses on best practices in demand forecasting literature has addressed the best practice concept under three different perspectives according to the universalistic perspective some forecasting practices are universally effective regardless of the context in which companies operate in the contingent perspective the effectiveness of forecasting practices depends on the specific kind of context each company faces a third perspective is the configurational one which asserts that there are synergistic effects among best practices in this work we compare these different perspectives by designing and testing different sets of propositions that underline the aforementioned perspectives analysis is conducted by collecting data of more than 500 companies in different countries via the 4th edition of the global manufacturing research group gmrg iv questionnaire the results demonstrate that each perspective has some empirical support

does asymmetric information matter in the early insurance market evidence from the auto insurance market in the late 1960s the performance of automobile insurance declined dramatically in japan in spite of rapid growth in the diffusion rate and the premiums were sharply raised several times in order to improve the situation this observation indicates the possible presence of adverse selection death spiral and provides an ideal situation for assessing informational asymmetry using bodily injury liability bil insurance data from 46 japanese prefectures over the period 1966 to 1975 this article tests two hypotheses of adverse selection i high risk drivers were more likely to join the bil insurance market and ii sharp premium increases drove low risk policyholders away various empirical analyses show that there is little evidence for either type of adverse selection we also test whether a risk misperception hypothesis can explain our results and find some evidence that the population density have a significantly positive impact on the demand for bil insurance an earlier version of this artic

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

the medicaid notch labor supply and welfare participation evidence from eligibility expansions i assess the impact of losing public health insurance on labor market decisions of women by examining a series of medicaid eligibility expansions targeted toward young children these targeted expansions severed the historical tie between afdc and medicaid eligibility the reforms allowed a mother s earnings to increase without losing public health insurance for her young children increasing the income limit for medicaid resulted in a decrease in afdc participation and an increase in labor force participation among these women the effects were large for ever married women and negligible for never married women

the pupil factory specialization and the production of human capital in schools i conducted a randomized field experiment in traditional public elementary schools in houston texas designed to test the potential productivity benefits of teacher specialization the average impact of encouraging schools to specialize their teachers on student achievement is 0 11 standard deviations per year on a combined index of math and reading test scores i argue that the results are consistent with a model in which the benefits of specialization driven by sorting teachers into a subset of subjects based on comparative advantage is outweighed by inefficient pedagogy due to having fewer interactions with each student though other mechanisms are possible

does public insurance crowd out private insurance the cost of expanding public sector health programs depends critically on the extent to which public eligibility will cover just the uninsured or will crowd out existing private insurance coverage we estimate the extent of crowd out arising from the expansions of medicaid to pregnant women and children over the 1987 1992 period we estimate that approximately 50 percent of the increase in medicaid coverage was associated with a reduction in private insurance coverage this occurred largely because employees took up employer based insurance less frequently there is also some evidence that employers contributed less for insurance and that workers dropped coverage of dependents

how has small group market reform affected employee health insurance coverage abstract in the early 1990s over 40 states passed legislation designed to limit a number of exclusionary practices by insurers in the small group market in order to improve the availability and affordability of health insurance to employees in small firms in this paper we address the effects of reform on the likelihood that workers are offered insurance have employment based coverage or are policyholders of an employment based plan we use differences in differences dd and differences in differences in differences ddd estimators to evaluate the differential effects of alternative reform measures on high and low risk workers we generally find little effect of reform on offer rates and find that in states with the most stringent reform employment based coverage and policyholder rates increased for high risk workers relative to low risk workers our results also indicate that the effects of reform varied significantly by the extent to which states adopted guaranteed issue

task specific experience and task specific talent decomposing the productivity of high school teachers abstract we use administrative panel data to decompose worker performance into components relating to general talent task specific talent general experience and task specific experience we consider the context of high school teachers in which tasks consist of teaching particular subjects in particular tracks using the timing of changes in the subjects and difficulty levels to which teachers are assigned to provide identifying variation we show that a substantial part of the productivity gains to teacher experience are actually subject specific similarly while three quarters of the variance in the permanent component of productivity among teachers is portable across subjects and levels there exist non trivial subject specific and level specific components counterfactual simulations suggest that maximizing the test score contribution of task specific experience and task specific talent can increase student performance by as much as 04 test score standard deviations relative to random assignment of teachers to classrooms

a hybrid seasonal autoregressive integrated moving average and quantile regression for daily food sales forecasting abstract in the retail stage of a food supply chain food waste and stock outs occur mainly due to inaccurate forecasting of sales which leads to incorrect ordering of products the time series sales in food retail industry are characterized by high volatility and skewness which vary by time so the interval forecasts are required by the retail companies to set appropriate inventory policy reorder point or safety stock level this paper attempts to develop a seasonal autoregressive integrated moving average with external variables sarimax model to forecast daily sales of a perishable food the process of fitting a sarimax model in this study involves i the development of seasonal autoregressive integrated moving average sarima model and ii combining the sarima model and the demand influencing factors using linear regression as the sarimax using multiple linear regression sarima mlr model produces only mean forecast the possibility of underestimation and overestimation is very high due to high service level peak and sparse sales in food retail industry therefore a hybrid sarima and quantile regression sarima qr is developed to construct high and low quantile predictions instead of extrapolating the quantiles from the mean point forecasts of sarima mlr model based on the assumption of normality the sarima qr model directly forecasts the quantiles the developed sarima mlr and sarima qr models are applied in modeling and forecasting of sales data i e the daily sales of banana from a discount retail store in lower bavaria germany the results show that the sarima mlr and qr models yield better forecasts at out sample data when compared to seasonal naive forecasting traditional sarima and multi layered perceptron neural network mlpnn models unlike the sarima mlr model the sarima qr model provides better prediction intervals and a deep insight into the effects of demand influencing factors for different quantiles

how to use aggregation and combined forecasting to improve seasonal demand forecasts standard forecasting methods that are designed to cope with seasonal demand often are no longer applicable in practice due to growing assortments and shorter product life cycles demand data may show too high variation or may be insufficient to construct reliable forecast models at the individual item level in this article we present alternative forecasting methods that are based on using demand information from a higher aggregation level and on combining forecasts sales data from two prominent dutch wholesalers are used to illustrate the drawbacks of the standard seasonal forecasting methods and to demonstrate the potential of the new methods the average reduction in forecast error in terms of mse turns out to be three times as large as reported in earlier studies on common seasonal patterns

forecasting quantiles of day ahead electricity load accurate load forecasting plays a crucial role in the decision making process of many market participants but probably is most important for the dispatch planning of an electricity market operator despite the competitive forecast accuracy achieved by existing point forecast models point forecasts can only provide limited information relating to the expected level of future load to account for the uncertainty of future load and provide a more complete picture of the future load conditions for dispatch planning purposes quantile forecasts can be useful this paper proposes a computationally efficient approach to forecasting the quantiles of electricity load which is then applied to forecasting in the national electricity market of australia the proposed model performs competitively in comparison with one industry standard and two recently proposed quantile forecasting methods one of the main advantages of the proposed approach is the ease with the number of covariates can be expanded this is a particularly important feature in the context of load forecasting where large numbers of important drivers are usually necessary to provide accurate load forecasts

equilibrium in competitive insurance markets with ex ante adverse selection and ex post moral hazard abstract existence of pure strategy equilibria is studied in health insurance markets that exhibit both ex ante adverse selection of the rothschild stiglitz wilson type and ex post hidden information moral hazard it is found that ex post moral hazard has two offsetting effects on the existence of equilibrium and that in general it is difficult to say whether an equilibrium is more or less likely to exist numerical simulations and an analytical example confirm that moral hazard may increase the likelihood of equilibrium these results are interpreted as evidence that health maintenance organization hmo markets could be less likely to exhibit stable equilibria than are fee for service insurance markets

unemployment insurance and precautionary saving abstract models of precautionary saving imply that households will hold more assets when faced with greater income uncertainty however previous empirical studies of income uncertainty have produced somewhat mixed support for the precautionary saving hypothesis in this paper we note that differences in the state contingent income stream available to workers through the unemployment insurance ui program provides an excellent source of variation for testing the presence of a precautionary savings motive simulations of a stochastic life cycle model suggest that a ui system similar to the type currently in place in the u s can lead to a significant reduction in the assets accumulated by a median worker moreover there is considerable variation in the ui benefit schedules for workers living in different states in the u s which provides an exogenous source of variation for empirically testing the precautionary saving hypothesis we carry out this test using data on expected ui benefit replacement rates and financial assets held by households in the survey of income and program participation our empirical results are consistent with the predictions of the model and suggest that reducing the ui benefit replacement rate by 50 percent would increase gross financial asset holdings by 14 percent or 241 for the average worker we also find empirical evidence that this crowd out effect of ui on household saving is stronger for those facing higher unemployment risk and weaker for older workers both of which are implications from our precautionary saving model

did community rating induce an adverse selection death spiral evidence from new york pennsylvania and connecticut using data from the 1987 to 1996 march current population surveys we find no evidence for the dire predictions of some that the imposition of pure community rating leads to a market wide reduction in insurance coverage by setting off an adverse selection death spiral specifically the percentage of individuals in small groups covered by health insurance did not fall in new york which enacted community rating legislation in 1993 relative to either pennsylvania which enacted no insurance reform or connecticut which enacted moderate insurance reforms without imposing community rating consistent with the predictions of the simple rothschild and stiglitz 1976 framework however we find that the new yorkreforms appear to have had a significant impact on the structure of the new yorkinsurance mark et specifically new yorkexperienced a dramatic shift away from indemnity insurance toward hmos while this shift tookplace during a period of nationwide increases in the percentage with managed care the increase in hmo penetration in new york s small group and individual markets was significantly greater than in pennsylvania or connecticut

accountability incentives and behavior the impact of high stakes testing in the chicago public schools the recent federal education bill no child left behind requires states to test students in grades 3 to 8 each year and to judge school performance on the basis of these test scores while intended to maximize student learning there is little empirical evidence about the effectiveness of such policies this study examines the impact of an accountability policy implemented in the chicago public schools in 1996 1997 using a panel of student level administrative data i find that math and reading achievement increased sharply following the introduction of the accountability policy in comparison to both prior achievement trends in the district and to changes experienced by other large urban districts in the mid west however for younger students the policy did not increase performance on a state administered low stakes exam an item level analysis suggests that the observed achievement gains were driven by increases in test specific skills and student effort i also find that teachers responded strategically to the incentives along a variety of dimensions by increasing special education placements preemptively retaining students and substituting away from low stakes subjects like science and social studies

adverse selection in health insurance markets evidence from state small group health insurance reforms abstract the past decade witnessed major changes in state laws governing the sale of health insurance to small employers states took measures to restrict insurers ability to distinguish between high and low risk customers because of concern about the low rate of coverage among workers in small firms the high prices in the small group market and the absence of federal health reform using both individual level and employer level data i test predictions about the effect of reforms on the employer provided health insurance market i estimate these effects for small firms and their workers using large firms and their workers in the same states as well as large and small firms and their workers in non reform states as comparison groups i find the reforms decreased the rate of employer coverage on average for workers in small firms by less than two percentage points within small firms low expenditure individuals experienced a larger decline in the rate of coverage through their employer while the coverage rate of high expenditure individuals rose slightly in some specifications there is also evidence that comprehensive reforms increased premiums slightly for small employers and that most of this increase was passed on to workers through higher employee contributions

a comparative study of linear and nonlinear models for aggregate retail sales forecasting abstract the purpose of this paper is to compare the accuracy of various linear and nonlinear models for forecasting aggregate retail sales because of the strong seasonal fluctuations observed in the retail sales several traditional seasonal forecasting methods such as the time series approach and the regression approach with seasonal dummy variables and trigonometric functions are employed the nonlinear versions of these methods are implemented via neural networks that are generalized nonlinear functional approximators issues of seasonal time series modeling such as deseasonalization are also investigated using multiple cross validation samples we find that the nonlinear models are able to outperform their linear counterparts in out of sample forecasting and prior seasonal adjustment of the data can significantly improve forecasting performance of the neural network model the overall best model is the neural network built on deseasonalized time series data while seasonal dummy variables can be useful in developing effective regression models for predicting retail sales the performance of dummy regression models may not be robust furthermore trigonometric models are not useful in aggregate retail sales forecasting

a decision support framework for exploring supply chain tradeoffs abstract producers of retail products continually need to determine how much of a particular product to produce the difficulty of judging correctly is compounded when the product has a short production sales interval and is made primarily for sale during the big winter shopping season e g around christmas holiday in an effort to minimize production and distribution costs decision makers would like to produce as early as possible but doing so would increase the risk of producing the wrong quantity good forecasting mitigates this problem and the use of agile supply chains allows the firm to produce later in the production sales interval both however add to the cost of production if the external environment is volatile then there would be increased uncertainty as to a desirable course of action this paper presents a simulation based decision support framework for exploring the tradeoffs in producing different quantities under a variety of supply chain configurations and alternate forecasting options given uncertain demand environments we provide an illustrative example to highlight these tradeoffs

redistribution by insurance market regulation analyzing a ban on gender based retirement annuities we illustrate how equilibrium screening models can be used to evaluate the economic consequences of insurance market regulation we calibrate and solve a model of the united kingdom s compulsory annuity market and examine the impact of gender based pricing restrictions we find that the endogenous adjustment of annuity contract menus in response to such restrictions can undo up to half of the redistribution from men to women that would occur with exogenous social security like annuity contracts our findings indicate the importance of endogenous contract responses and illustrate the feasibility of employing theoretical insurance market equilibrium models for quantitative policy analysis

do low income housing subsidies increase the occupied housing stock abstract a necessary condition for justifying a policy such as subsidized low income housing either via tenant based rental assistance or construction of public or private projects is that it has a real effect on market outcomes in this paper we examine one aspect of the real effect of subsidized housing does it increase the housing stock if subsidized housing raises the quantity of occupied housing per capita either more people are finding housing or they are being housed less densely on the other hand if subsidized housing merely crowds out equivalent quality low income housing that otherwise would have been provided by the private sector the housing policy may have little real effect on housing consumption using both census place and msa level data from the decennial census and from the department of housing and urban development we ask whether housing markets with more subsidized housing also have more total housing after accounting for housing demand we find that government financed units raise the total number of units in a market although on average one government subsidized unit adds only one third to one half of a unit to the total housing stock there is less crowd out in more populous markets and more crowd out in places where there is less excess demand for subsidized housing as measured by the number of government financed units per eligible person tenant based housing programs such as section 8 certificates and vouchers seem to be more effective than project based programs at targeting subsidized housing units to people who otherwise would not have their own

performance analysis of demand planning approaches for aggregating forecasting and disaggregating interrelated demands a synchronized and responsive flow of materials information funds processes and services is the goal of supply chain planning demand planning which is the very first step of supply chain planning determines the effectiveness of manufacturing and logistic operations in the chain propagation and magnification of the uncertainty of demand signals through the supply chain referred to as the bullwhip effect is the major cause of ineffective operation plans therefore a flexible and robust supply chain forecasting system is necessary for industrial planners to quickly respond to the volatile demand appropriate demand aggregation and statistical forecasting approaches are known to be effective in managing the demand variability this paper uses the bivariate var 1 time series model as a study vehicle to investigate the effects of aggregating forecasting and disaggregating two interrelated demands through theoretical development and systematic analysis guidelines are provided to select proper demand planning approaches a very important finding of this research is that disaggregation of a forecasted aggregated demand should be employed when the aggregated demand is very predictable through its positive autocorrelation moreover the large positive correlation between demands can enhance the predictability and thus result in more accurate forecasts when statistical forecasting methods are used

non stationary demand forecasting by cross sectional aggregation in this paper the relative effectiveness of top down td versus bottom up bu approaches is compared for cross sectionally forecasting aggregate and sub aggregate demand we assume that the sub aggregate demand follows a non stationary integrated moving average ima process of order one and a single exponential smoothing ses procedure is used to extrapolate future requirements such demand processes are often encountered in practice and ses is one of the standard estimators used in industry in addition to being the optimal estimator for an ima process theoretical variances of forecast error are derived for the bu and td approach in order to contrast the relevant forecasting performances the theoretical analysis is supported by an extensive numerical investigation at both the aggregate and sub aggregate level in addition to empirically validating our findings on a real dataset from a european superstore the results demonstrate the increased benefit resulting from cross sectional forecasting in a non stationary environment than in a stationary one valuable insights are offered to demand planners and the paper closes with an agenda for further research in this area

smooth quantile based modeling of brand sales price and promotional effects from retail scanner panels semiparametric quantile regression is employed to flexibly estimate sales response for frequently purchased consumer goods using retail store level data we compare the performance of models with and without monotonic smoothing for fit and prediction accuracy we find that a flexible models with monotonicity constraints imposed on price effects dominate both in sample and out of sample comparisons while being robust even at the boundaries of the price distribution when data is sparse b quantile based confidence intervals are much more accurate compared to least squares based intervals c specifications reflecting that managers may not have exact knowledge about future competitive pricing perform extremely well

the value of medicaid interpreting results from the oregon health insurance experiment we develop frameworks for welfare analysis of medicaid and apply them to the oregon health insurance experiment across different approaches we estimate low income uninsured adults willingness to

government decision making and the incidence of federal mandates abstract this paper analyzes the effects of federally mandated program changes on state spending and revenues incorporating and evaluating the predictive value of several common theories of the state decision making process using several sources of exogenous increases in public medical spending i estimate that the entire state portion of the burden of mandated spending is borne by decreases in other public welfare spending while federal mandates may influence the composition of benefits at the state level it is much more difficult for them to change the total level of state transfers comparison of state reactions to different shocks suggests that these reductions are due in part to the substitutability of programs in the voter utility function but also in part to the stickiness of spending within budget categories states with greater racial differences between recipients and voters and states with less generous neighbors reduce other public welfare spending by even more alleviating the burden the medical expansions imposed on their taxpayers mandates may thus serve only to increase inequality across states

competition leverage how the demand side affects optimal risk adjustment we study optimal risk adjustment in imperfectly competitive health insurance markets when high risk consumers are less likely to switch insurer than low risk consumers insurers then have an incentive to select even if risk adjustment perfectly corrects for cost differences to achieve first best risk adjustment should overcompensate insurers for serving high risk agents second we identify a trade off between efficiency and consumer welfare reducing the difference in risk adjustment subsidies increases consumer welfare by leveraging competition from the elastic low risk market to the less elastic high risk market third mandatory pooling can increase consumer surplus further at the cost of efficiency

averages of forecasts some empirical results an alternative to using a single forecasting method is to average the forecasts obtained from several methods in this paper we investigate empirically the impact of the number and choice of forecasting methods on the accuracy of simple averages it is concluded that the forecasting accuracy improves and that the variability of accuracy among different combinations decreases as the number of methods in the average increases thus combining forecasts seems to be a reasonable practical alternative when as is often the case a true model of the data generating process or a single best forecasting method cannot be or is not for whatever reasons identified

a semi parametric approach for estimating critical fractiles under autocorrelated demand abstract forecasting critical fractiles of the lead time demand distribution is an important problem for operations managers making newsvendor type inventory decisions in this paper we propose a semi parametric approach to forecasting the critical fractile when demand is serially correlated starting from a user defined but potentially misspecified forecasting model we use historical demand data to generate empirical forecast errors of this model these errors are then used to 1 parametrically correct for any bias in the point forecast conditional on the recent demand history and 2 non parametrically estimate the critical fractile of the demand distribution without imposing distributional assumptions we present conditions under which this semi parametric approach provides a consistent estimate of the critical fractile and evaluate its finite sample properties using simulation and real data for retail inventory planning

strategic interaction among governments in the provision of a global public good abstract how do governments respond to other governments when providing a global public good using data from 2007 to 2014 on medical research funding for infectious and parasitic diseases we examine how governments and foundations in 41 countries respond to funding changes by the us government which accounts for half of funding for these diseases because funding across governments might be positively correlated due to unobserved drivers they have in common we use variation in the representation of research intensive universities on us congressional appropriations committees as an instrument for us funding we find that a 10 increase in us government funding for a disease is associated with a 2 to 3 reduction in funding for that disease by another government in the following year

forecasting daily supermarket sales using exponentially weighted quantile regression inventory control systems typically require the frequent updating of forecasts for many different products in addition to point predictions interval forecasts are needed to set appropriate levels of safety stock the series considered in this paper are characterised by high volatility and skewness which are both time varying these features motivate the consideration of forecasting methods that are robust with regard to distributional assumptions the widespread use of exponential smoothing for point forecasting in inventory control motivates the development of the approach for interval forecasting in this paper we construct interval forecasts from quantile predictions generated using exponentially weighted quantile regression the approach amounts to exponential smoothing of the cumulative distribution function and can be viewed as an extension of generalised exponential smoothing to quantile forecasting empirical results are encouraging with improvements over traditional methods being particularly apparent when the approach is used as the basis for robust point forecasting

adverse selection in annuity markets evidence from the british life annuity act of 1808 abstract we study adverse selection using data from an 1808 act of british parliament that effectively opened a market for life annuities our analysis indicates significant selection effects the evidence for adverse selection is strongest for a sub sample of annuitants whose annuities were purchased by profit seeking speculators a sub sample in which advantageous selection resulting from multi dimensional heterogeneity is unlikely to have been significant these results support the view that adverse selection can be masked by advantageous selection in empirical studies of standard insurance markets

forecasting with multivariate temporal aggregation the case of promotional modelling demand forecasting is central to decision making and operations in organisations as the volume of forecasts increases for example due to an increased product customisation that leads to more skus being traded or a reduction in the length of the forecasting cycle there is a pressing need for reliable automated forecasting conventionally companies rely on a statistical baseline forecast that captures only past demand patterns which is subsequently adjusted by human experts to incorporate additional information such as promotions although there is evidence that such process adds value to forecasting it is questionable how much it can scale up due to the human element instead in the literature it has been proposed to enhance the baseline forecasts with external well structured information such as the promotional plan of the company and let experts focus on the less structured information thus reducing their workload and allowing them to focus where they can add most value this change in forecasting support systems requires reliable multivariate forecasting models that can be automated accurate and robust this paper proposes an extension of the recently proposed muliple aggregation prediction algorithm mapa which uses temporal aggregation to improve upon the established exponential smoothing family of methods mapa is attractive as it has been found to increase both the accuracy and robustness of exponential smoothing the extended multivariate mapa is evaluated against established benchmarks in modelling a number of heavily promoted products and is found to perform well in terms of forecast bias and accuracy furthermore we demonstrate that modelling time series using multiple temporal aggregation levels makes the final forecast robust to model misspecification

long memory economic policy uncertainty and forecasting us inflation a bayesian varfima approach abstractwe compare inflation forecasts of a vector autoregressive fractionally integrated moving average varfima model against standard forecasting models u s inflation forecasts improve when controlling for persistence and economic policy uncertainty epu importantly the varfima model comprising of inflation and epu outperforms commonly used inflation forecast models

demand forecasting with high dimensional data the case of sku retail sales forecasting with intra and inter category promotional information in marketing analytics applications in or the modeler often faces the problem of selecting key variables from a large number of possibilities for example sku level retail store sales are affected by inter and intra category effects which potentially need to be considered when deciding on promotional strategy and producing operational forecasts but no research has yet put this well accepted concept into forecasting practice an obvious obstacle is the ultra high dimensionality of the variable space this paper develops a four steps methodological framework to overcome the problem it is illustrated by investigating the value of both intra and inter category sku level promotional information in improving forecast accuracy the method consists of the identification of potentially influential categories the building of the explanatory variable space variable selection and model estimation by a multistage lasso regression and the use of a rolling scheme to generate forecasts the success of this new method for dealing with high dimensionality is demonstrated by improvements in forecasting accuracy compared to alternative methods of simplifying the variable space the empirical results show that models integrating more information perform significantly better than the baseline model when using the proposed methodology framework in general we can improve the forecasting accuracy by 12 6 percent over the model using only the sku s own predictors but of the improvements achieved 95 percent of it comes from the intra category information and only 5 percent from the inter category information the substantive marketing results also have implications for promotional category management

dynamic inefficiencies in an employment based health insurance system theory and evidence we investigate the effects of the institutional settings of the us health care system on individuals life cycle medical expenditures health is a form of general human capital labor turnover and labor market frictions prevent an employer employee pair from capturing the entire surplus from investment in an employee s health thus the pair underinvests in health during working years thereby increasing medical expenditures during retirement we provide empirical evidence consistent with the comparative statics predictions of our model using the medical expenditure panel survey meps and the health and retirement study hrs our estimates suggest significant inefficiencies in health investment in the united states

the complementarity between risk adjustment and community rating distorting market outcomes to facilitate redistribution abstract we analyze optimal risk adjustment in competitive health insurance markets when insurers have better information on their customers risk profiles than the sponsor of health insurance in the optimal scheme the sponsor uses reinsurance to screen insurers with bad and good risks in order to lower premiums for enrollees with high expected healthcare costs we then explore the effects of adding a community rating requirement to complement this risk adjustment scheme with community rating insurers have incentives to distort contract generosities to cherry pick low cost consumers however the reduced generosity for low cost types makes screening through reinsurance easier allowing the sponsor to redistribute more when costs for reinsurance are low or the sponsor s bias towards high cost consumers is high community rating dominates risk rating

innovation and the welfare effects of public drug insurance rewarding inventors with inefficient monopoly power has long been regarded as the price of encouraging innovation prescription drug insurance escapes that trade off and achieves an elusive goal lowering static deadweight loss without reducing incentives for innovation as a result of this feature the public provision of drug insurance can be welfare improving even for risk neutral and purely self interested consumers the design of insurers cost sharing schedules can either reinforce or mitigate this result schedules that impose higher consumer cost sharing requirements on more expensive drugs help ensure that insurance subsidies translate into higher utilization rather than pure increases in manufacturer profits moreover some degree of price negotiation with manufacturers is likely to be welfare improving but the optimal degree depends on the size of such transactions costs as well as the social cost of weakening innovation incentives by lowering innovator profits these results have practical implications for the evaluation of public drug insurance programs like the us medicaid and medicare part d programs along with european insurance schemes

subsidies and crowding out a double hurdle model of fertilizer demand in malawi this article uses a double hurdle model with panel data from malawi to investigate how fertilizer subsidies affect farmer demand for commercial fertilizer the article controls for potential endogeneity caused by the nonrandom targeting of fertilizer subsidy recipients results show that on average 1 additional kilogram of subsidized fertilizer crowds out 0 22 kg of commercial fertilizer but crowding out ranges from 0 18 among the poorest farmers to 0 30 among relatively nonpoor farmers this indicates that targeting fertilizer subsidies to the rural poor is likely to maximize the contribution of the subsidy program to total fertilizer use

the division of labor coordination costs and knowledge this paper considers specialization and the division of labor a more extensive division of labor raises productivity because returns to the time spent on tasks are usually greater to workers who concentrate on a narrower range of skills the traditional discussion of the division of labor emphasizes the limitations to specialization imposed by the extent of the market we claim that the degree of specialization is more often determined by other considerations especially emphasized are various costs of coordinating specialized workers who perform complementary tasks and the amount of general knowledge available

the mortgage interest deduction and its impact on homeownership decisions abstract this paper examines the impact of the combined u s state and federal mortgage interest deduction mid on homeownership attainment using data from 1984 to 2007 and exploiting variation in the subsidy arising from changes in the mid within and across states over time we test whether capitalization of the mid into house prices offsets the positive effect on homeownership we find that the mid boosts homeownership attainment only of higher income households in less tightly regulated housing markets in more restrictive places an adverse effect exists the mid is an ineffective policy to promote homeownership and improve social welfare

the incidence of mandated maternity benefits i consider the labor market effects of mandates which raise the costs of employing a demographically identifiable group the efficiency of these policies will be largely dependent on the extent to which their costs are shifted to group specific wages i study several state and federal mandates which stipulated that childbirth be covered comprehensively in health insurance plans raising the relative cost of insuring women of childbearing age i find substantial shifting of the costs of these mandates to the wages of the targeted group correspondingly i find little effect on total labor input for that group jel 118 j32 h51 in an era of tight fiscal budget constraints mandating employer provision of workplace benefits to employees is an attractive means for a government to finance its policy agenda consequently in recent years there has been a growth of interest in mandated benefits as a tool of social policy for example the centerpiece of president bill clinton s health care proposal is mandated employer provision of health insurance and more than 20 states have man

estimating welfare in insurance markets using variation in prices we provide a graphical illustration of how standard consumer and producer theory can be used to quantify the welfare loss associated with inefficient pricing in insurance markets with selection we then show how this welfare loss can be estimated empirically using identifying variation in the price of insurance such variation together with quantity data allows us to estimate the demand for insurance the same variation together with cost data allows us to estimate how insurers costs vary as market participants endogenously respond to price the slope of this estimated cost curve provides a direct test for both the existence and the nature of selection and the combination of demand and cost curves can be used to estimate welfare we illustrate our approach by applying it to data on employerprovided health insurance from one specific company we detect adverse selection but estimate that the quantitative welfare implications associated with inefficient pricing in our particular application are small in both absolute and relative terms

distributions of forecasting errors of forecast combinations implications for inventory management inventory control systems rely on accurate and robust forecasts of future demand to support decisions such as setting of safety stocks the combination of multiple forecasts is shown to be effective not only in reducing forecast errors but also in being less sensitive to limitations of a single model research on forecast combination has primarily focused on improving accuracy largely ignoring the overall shape and distribution of forecast errors nonetheless these are essential for managing the level of aversion to risk and uncertainty for companies this study examines the forecast error distributions of base and combination forecasts and their implications for inventory performance it explores whether forecast combinations transform the forecast error distribution towards desired properties for safety stock calculations typically based on the assumption of normally distributed errors and unbiased forecasts in addition it considers the similarity between in and out of sample characteristics of such errors and the impact of different lead times the effects of established combination methods are explored empirically using a representative set of forecasting methods and a dataset of 229 weekly demand series from a leading household and personal care uk manufacturer findings suggest that forecast combinations make the in and out of sample behaviour more consistent requiring less safety stock on average than base forecasts furthermore we find that using in sample empirical error distributions of combined forecasts approximates well the out of sample ones in contrast to base forecasts

crowd out effects of place based subsidized rental housing new evidence from the lihtc program abstract since its inception in 1987 the low income housing tax credit lihtc program has ballooned into the largest ever source of subsidized construction of low income housing in the united states accounting for one third of all recent multi family rental construction this paper examines the crowd out effects of this increasingly important source of low moderate income housing to do so we analyze the impact of lihtc construction at three different levels of geography msa county and 10 mile radius circles this allows us to employ increasingly extensive geographic fixed effects that help to difference away unobserved factors political variables are also used as instruments to further facilitate identification in all of our models iv estimates yield substantially greater crowd out than ols confirming the endogenous attraction of lihtc development to areas ripe for new construction our most robust iv estimates indicate that nearly 100 of lihtc development is offset by a reduction in the number of newly built unsubsidized rental units although the confidence band around this point estimate allows for less dramatic assessments additional estimates suggest that lihtc development has a much more moderate impact on construction of owner occupied housing but these estimates are imprecise overall while lihtc development may well affect the location of low moderate income rental housing opportunities our estimates suggest that the impact of the program on the number of newly developed rental housing units appears to be small

social insurance private health insurance and individual welfare abstract this paper studies the impact of social insurance on individual choices and welfare in a dynamic general equilibrium model with uncertain medical expenses and individual health insurance choices i find that social insurance modeled as the combination of a minimum consumption floor and the medicaid program does not only distort saving and labor supply decisions but also has a large crowding out effect on the demand for private health insurance however despite the distorting effects the net welfare consequence of eliminating social insurance is still negative in most cases in addition the large crowding out effect on private health insurance suggests that the existence of social insurance programs may be one reason why some americans do not buy any health insurance

demand forecasting for multiple slow moving items with short requests history and unequal demand variance modeling the lead time demand for the multiple slow moving inventory items in the case when the available requests history is very short is a challenge for inventory management the classical forecasting technique which is based on the aggregation of the stock keeping units to overcome the mentioned historical data peculiarity is known to lead to very poor performance in many cases important for industrial applications an alternative approach to the demand forecasting for the considered problem is based on the bayesian paradigm when the initially developed population averaged demand probability distribution is modified for each item using its specific requests history this paper follows this approach and presents a new model which relies on the beta distribution as a prior for the request probability and allows to account for disparity in variance of demand between different stock keeping units to estimate the model parameters a special computationally effective technique based on the generalized method of moments is developed simulation results indicate the superiority of the proposed model over the known ones while the computational burden does not increase

where do the sick go health insurance and employment in small and large firms this research was supported by a grant from the economic research initiative on the uninsured at the university of michigan

paying for health insurance the trade off between competition and adverse selection we use data on health plan choices by employees of harvard university to compare the benefits of insurance competition with the costs of adverse selection moving to a voucher type system induced significant adverse selection with a welfare loss of 2 to 4 percent of baseline spending but increased competition reduced harvard s premiums by 5 to 8 percent the premium reductions came from insurer profits so while harvard was better off the net effect for society was only the adverse selection loss adverse selection can be minimized by adjusting voucher amounts for individual risk we discuss how such a system would work governments are increasingly turning to market forces as a way to limit the cost of social insurance traditionally social insurance programs were operated as nonmarket goods governments mandated participation in a central program collected revenues to finance the program and ran the insurance system there was no role for competition among suppliers in providing the basic benefit as the costs of social insurance have increased however the centralized model of social insurance is coming under increasing strain in the united states for example recent proposals have called for replacing the medicare program with a health care voucher for the elderly aaron and reischauer 1995 cutler 1996 the voucher would guarantee people a basic insurance plan but the plans would be privately run competition among plans would generate plan premiums and enrollments similarly longstanding proposals for social security reform have called for replacing the current system with a system of individual accounts where people would make saving investment and annuitization decisions on their own advisory council on social security 1996 feldstein 1996 the trend is not just domestic in the united kingdom the national health service has moved to encourage more competition in recent years with the establishment of hospital trusts that bid for patients and partially fixed payments to physicians

community rating and the market for private non group health insurance abstract prior research on adverse selection in health insurance markets has found only mixed evidence for adverse selection in group settings we examine the impact of state community rating regulations enacted in the 1990s which greatly limited insurers ability to risk rate premiums to determine if adverse selection is more evident in non group insurance markets using data from large national surveys we find evidence of a shift to a less healthy pool of non group enrollees as a consequence of community rating community rating made healthy people 20 to 60 less likely to be insured by non group health insurance in addition we found evidence that young and healthy people were 20 to 30 more likely to be uninsured as a result of community rating we also find evidence that individuals in poor health were 35 to 50 more likely to be insured in the non group market but only limited evidence suggesting that persons in poor health were less likely to be uninsured our results are further supported by findings suggesting that non group enrollees were sicker as a result of the community rating laws lastly we find evidence suggesting that hmo penetration in the non group market increased disproportionately in states that implemented community rating relative to states that did not

industrial production volatility and the supply chain abstract the issue of production volatility is important to firms interested in managing their supply chain this paper empirically estimates the volatility of industrial production using the garch and egarch time series models three questions are addressed can volatility be predicted is the effect of unexpected changes in production on volatility asymmetric and how persistent is volatility following a production disturbance the results indicate that production volatility is time varying and can be predicted in the majority of cases examined and that overestimates of production lead to greater increases in volatility than do underestimates

selection in health insurance markets and its policy remedies selection adverse or advantageous is the central problem that inhibits the smooth efficient functioning of competitive health insurance markets even and perhaps especially when consumers are well informed decision makers and insurance markets are highly competitive and offer choice such markets may function inefficiently due to risk selection selection can cause markets to unravel with skyrocketing premiums and can cause consumers to be under or overinsured in its simplest form adverse selection arises due to the tendency of those who expect to incur high health care costs in the future to be the most motivated purchasers the costlier enrollees are more likely to become insured rather than to remain uninsured and conditional on having health insurance the costlier enrollees sort themselves to the more generous plans in the choice set these dual problems represent the primary concerns for policymakers designing regulations for health insurance markets in this essay we review the theory and evidence concerning selection in competitive health insurance markets and discuss the common policy tools used to address the problems it creates we emphasize the two markets that seem especially likely to be targets of reform in the short and medium term medicare advantage the private plan option available under medicare and the state level individual insurance markets

a model for selecting the appropriate level of aggregation in forecasting processes abstract demand forecasting is a major issue in several industrial sectors a relevant choice for companies is the proper level of forecast aggregation forecasters need to properly identify what is the object of the forecasting process in terms of time bucket e g forecasts are produced on a daily level or on weekly one set of items the demand refers to e g single item or group of items set of locations the demand refers to e g single store or chain of stores managers can follow two basic approaches on the one hand they can adopt a detailed forecasting approach i e they can forecast demand for the item at the store by simply looking at the demand for the specific item store on the other hand they can adopt an aggregated forecasting approach in this paper we aim at figuring out what is the balance between the strengths and weaknesses of these two options and to identify the contingent variables that might lead managers to adopt one approach rather than the other in this paper we study the aggregation across locations by evaluating the components of forecasting error under the assumption of stationary demand finally we suggest metrics that one can adopt to support the choice of the appropriate forecasting process thus providing help to managers in defining the proper level of aggregation for a specific situation

the effect of medicare part d on pharmaceutical prices and utilization prescription drug expenditures represent the most rapidly growing component of health care spending increasing from 5 percent of health care spending in 1980 to more than 10 percent by 2005 centers for medicare and medicaid services cms 2007a further almost 60 percent of all prescriptions in the united states are filled for beneficiaries of medicare medicaid and other government programs rapid innovation in new pharmaceuticals has contributed substantially to quality of life and longevity in the us frank lichtenberg 1996 these facts combined indicate that government procurement schemes are critical both in determining government expenditure on pharmaceuticals and in stimulating innovation of new treatments in this paper we show that the institutions and mechanisms used by the government to pur chase prescription drugs can strongly affect market outcomes by institutions we have in mind large buyer groups structured incentives for patients to consume certain products and the devel opment and use of formularies a formulary is a mechanism that allows a buyer to identify a therapeutically similar treatment as a viable substitute for a patented treatment and to create price competition due to the ability to substitute away from the more expensive product when bargaining with the seller of a patented product the ability to shift demand to a substitute drug is a powerful negotiating tool our paper provides evidence for what we consider a surprising outcome in the case of the new prescription drug program for medicare enrollees moving consumers from cash paying status to membership in an insured group lowers optimal prices for branded prescription drugs below what they otherwise would be this is surprising because the standard effect of insurance is to create inelastic demand and therefore elicit higher prices from a seller with market power duggan and scott morton 2006 however the insurers that we study bundle insurance with a formulary and other mechanisms to create elastic demand an individual consumer typically does not know which drugs are acceptable therapeutic substitutes the consumer s physician typi cally has poor knowledge of prices especially negotiated prices and any one consumer is too small a share of demand to negotiate with a pharmaceutical company a prescription drug plan can potentially surmount all three hurdles our evidence leads us to conclude that the formulary and other mechanisms perform the spe cial role of allowing buyers to move market share among drugs with patent protection thereby raising cross price elasticities and lowering purchase prices or reducing price increases for branded drugs this result contrasts with the common intuition that an uninsured consumer

macroeconomic forecasting using diffusion indexes this article studies forecasting a macroeconomic time series variable using a large number of predictors the predictors are summarized using a small number of indexes constructed by principal component analysis an approximate dynamic factor model serves as the statistical framework for the estimation of the indexes and construction of the forecasts the method is used to construct 6 12 and 24 monthahead forecasts for eight monthly u s macroeconomic time series using 215 predictors in simulated real time from 1970 through 1998 during this sample period these new forecasts outperformed univariate autoregressions small vector autoregressions and leading indicator models

do financial variables help forecasting inflation and real activity in the euro area abstract this paper uses a large data set consisting of 447 monthly macroeconomic time series concerning the main countries of the euro area to simulate out of sample predictions of the euro area industrial production and the harmonized inflation index and to evaluate the role of financial variables in forecasting we considered two models which allow forecasting based on large panels of time series forni et al rev econom statist 82 2000 540 mimeo 2001b and stock and watson mimeo 1999 performance of both models were compared to that of a simple univariate ar model results show that multivariate methods outperform univariate methods for forecasting inflation at one three six and twelve months and industrial production at one and three months we find that financial variables do help forecasting inflation but do not help forecasting industrial production

forecasting aggregate retail sales the case of south africa abstract forecasting aggregate retail sales may improve portfolio investors ability to predict movements in the stock prices of retail chains this paper uses 26 23 single and 3 combination forecasting models to forecast south africa s aggregate seasonal retail sales we use data from 1970 01 2012 05 with 1987 01 2012 05 as the out of sample period unlike the previous literature on retail sales forecasting we not only look at a wide array of linear and nonlinear models but also generate multi step ahead forecasts using a real time recursive estimation scheme over the out of sample period to better mimic the practical scenario faced by economic agents making retailing decisions in addition we deviate from the uniform symmetric quadratic loss function typically used in forecast evaluation exercises by considering loss functions that overweight the forecast error in booms and recessions focusing on the results of single models alone shows that their performances differ greatly across forecast horizons and for different weighting schemes with no unique model performing the best across various scenarios however combination forecast models especially the discounted mean square forecast error method which weighs current information more than past not only produced better forecasts but were also largely unaffected by business cycles and time horizons this result along with individual nonlinear models performing better than linear models led us to conclude that theoretical research on retail sales should look at developing dynamic stochastic general equilibrium models that not only incorporate learning behavior but also allow the behavioral parameters of the model to be state dependent to account for regime switching behavior across alternative states of the economy

the impact of aggregation level on forecasting performance abstract most operations decisions are based on some kind of forecast of future demand thus forecasting is definitely a very traditional area in the operations and inventory management literature while literature concerning forecast explores the adoption of various qualitative and quantitative methods this paper tries to design new solutions to improve forecasting accuracy by focusing on the forecasting process that uses such algorithms in particular when forecasting demand one should always make clear exactly what he she is trying to forecast in terms of the time bucket i e the period of time over which demand is aggregated the forecasting horizon the set of items the demand refers to e g forecasting demand for a single item can be much harder than forecasting demand for a group of items the set of locations the demand refers to e g demand at the single store level is much less predictable than the demand for a whole chain of stores traditionally these features of the final output of forecasting also influence the forecasting process indeed when one wants to forecast demand at single store single item single day level it seems natural to analyse demand and causal factors at the same level of aggregation on the contrary in this paper we aim at showing that first of all often aggregating and or disaggregating data in the forecasting process can lead to substantial improvements second the choice of the appropriate level of aggregation depends on the underlying demand generation process in addition most forecasting algorithms tend to focus on a single demand variable on the contrary we can analyse analogous time series to improve the effectiveness of the forecasting process clustering techniques can be used to identify such homologous time series such clusters of homologous time series can provide on the one hand the sample size required to gain good statistical confidence and on the other hand relatively homogeneous data in the paper we use sales data from a food retailer at a very detailed level to test our hypotheses this claims for relevance for both practitioners and researchers

caviar conditional autoregressive value at risk by regression quantiles value at risk var has become the standard measure of market risk employed by financial institutions for both internal and regulatory purposes var is defined as the value that a portfolio will lose with a given probability over a certain time horizon usually one or ten days despite its conceptual simplicity its measurement is a very challenging statistical problem and none of the methodologies developed so far give satisfactory solutions interpreting the var as the quantile of future portfolio values conditional on current information we propose a new approach to quantile estimation which does not require any of the extreme assumptions invoked by existing methodologies such as normality or i i d returns the conditional autoregressive value at risk or caviar model moves the focus of attention from the distribution of returns directly to the behavior of the quantile we specify the evolution of the quantile over time using a special type of autoregressive process and use the regression quantile framework introduced by koenker and bassett to determine the unknown parameters since the objective function is not differentiable we use a differential evolutionary genetic algorithm for the numerical optimization utilizing the criterion that each period the probability of exceeding the var must be independent of all the past information we introduce a new test of model adequacy the dynamic quantile test applications to simulated and real data provide empirical support to this methodology and illustrate the ability of these algorithms to adapt to new risk environments

health insurance market reform and employee compensation the case of pure community rating in new york abstract pure community rating which was enacted to improve access to health insurance in new york s small group market in 1993 prevents carriers from charging different premiums based on the ages of a firm s workers if small firms were adjusting compensation packages prior to reform to offset higher health care costs of older workers then community rating could lead to greater relative wages for older workers post reform and not necessarily induce adverse selection that results in changes in who is insured i present evidence showing that relative wages of older workers in small firms increased in comparison with other states and with large firms within new york following reform

take it to the limit innovative cvar applications to extreme credit risk measurement abstract the global financial crisis gfc demonstrated the devastating impact of extreme credit risk on global economic stability we develop four credit models to better measure credit risk in extreme economic circumstances by applying innovative conditional value at risk cvar techniques to structural models called xtreme s transition models xtreme t quantile regression models xtreme q and the author s unique itransition model xtreme i which incorporates industry factors into transition matrices we find the xtreme s and xtreme q models to be the most responsive to changing market conditions the paper also demonstrates how the models can be used to determine capital buffers required to deal with extreme credit risk

training wages and sample selection estimating sharp bounds on treatment effects this paper empirically assesses the wage effects of the job corps program one of the largest federally funded job training programs in the u s even with the aid of a randomized experiment the impact of a training program on wages is difficult to study because of sample selection a pervasive problem in applied microeconometric research wage rates are only observed for those who are employed and employment status itself may be affected by the training program this paper develops an intuitive trimming procedure for bounding average treatment effects in the presence of sample selection in contrast to existing methods the procedure requires neither exclusion restrictions nor a bounded support for the outcome of interest identification results estimators and their asymptotic distribution are presented the bounds suggest that the program raised wages consistent with the notion that the job corps raises earnings by increasing human capital rather than solely through encouraging work the estimator is generally applicable to typical treatment evaluation problems in which there is nonrandom sample selection attrition copyright wiley blackwell