tax exporting regional economic growth and welfare abstract long run exporting and importing of regional taxes is assessed theoretically and empirically using a six region nonlinear general equilibrium model of the united states the relationships between tax exporting and three aggregate measures of regional change value added welfare of all residents and welfare of original residents only are examined empirically the ability of states to adopt tax structures that successfully impose more of a burden on out of state residents does not necessarily promote regional economic growth or welfare and evaluating tax policy based on its ability to promote economic growth may be misleading if regional welfare is the primary objective

answering the skeptics yes standard volatility models do provide accurate forecasts a voluminous literature has emerged for modeling the temporal dependencies in financial market volatility using arch and stochastic volatility models while most of these studies have documented highly significant in sample parameter estimates and pronounced intertemporal volatility persistence traditional ex post forecast evaluation criteria suggest that the models provide seemingly poor volatility forecasts contrary to this contention we show that volatility models produce strikingly accurate interdaily forecasts for the latent volatility factor that would be of interest in most financial applications new methods for improved ex post interdaily volatility measurements based on high frequency intradaily data are also discussed

idiosyncratic variation of treasury bill yields i document a dramatic increase in the importance of two types of variation in treasury bill yields beginning in the early 1980s the first is idiosyncratic variation in individual short maturity less than three months bill yields the second is a common component in treasury bill yields that is not shared by yields on other instruments such as short maturity privately issued instruments or longer maturity treasury notes and bonds some evidence suggests the first type reflects increased market segmentation these results have important implications for the calibration and testing of no arbitrage term structure models and interpreting tests of the expectations hypothesis united states treasury bill yields play a central role in economists efforts to understand the behavior of financial markets the focus on treasury bills is driven by the belief that bill yields can be viewed as benchmarks from which yields on other debt instruments are derived for example in no arbitrage models of the default free term structure the stochastic properties of the hypothetical instantaneous interest rate determine bond prices researchers often construct and evaluate these models using short maturity bill yields as proxies for instantaneous interest rates similarly bill yields are frequently used to test the expectations hypothesis of the term structure 2 economists standard pricing models for default risky securities also view treasury yields as building blocks in such models yields on default risky securities depend at least in part on the yields of default free securities and the underlying stochastic default process therefore yields on treasury bills have been used in studies of the effects of monetary policy on the business cycle not because bills are intrinsically critical to the economy but because

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

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

real time density forecasts from bayesian vector autoregressions with stochastic volatility central banks and other forecasters are increasingly interested in various aspects of density forecasts however recent sharp changes in macroeconomic volatility including the great moderation and the more recent sharp rise in volatility associated with increased variation in energy prices and the deep global recession pose significant challenges to density forecasting accordingly this paper examines with real time data density forecasts of u s gdp growth unemployment inflation and the federal funds rate from bayesian vector autoregression bvar models with stochastic volatility the results indicate that adding stochastic volatility to bvars materially improves the real time accuracy of density forecasts this article has supplementary material online

forecasting portfolio value at risk with nonparametric lower tail dependence estimates abstract we propose to forecast the value at risk of bivariate portfolios using copulas which are calibrated on the basis of nonparametric sample estimates of the coefficient of lower tail dependence we compare our proposed method to a conventional copula garch model where the parameter of a clayton copula is estimated via canonical maximum likelihood the superiority of our proposed model is exemplified by analyzing a data sample of nine different bivariate and one nine dimensional financial portfolio a comparison of the out of sample forecasting accuracy of both models confirms that our model yields economically significantly better value at risk forecasts than the competing parametric calibration strategy

do banks overstate their value at risk abstract this paper is the first empirical study of banks risk management systems based on non anonymous daily value at risk var and profit and loss data using actual data from the six largest canadian commercial banks we uncover evidence that banks exhibit a systematic excess of conservatism in their var estimates the data used in this paper have been extracted from the banks annual reports using an innovative matlab based data extraction method out of the 7354 trading days analyzed in this study there are only two exceptions i e days when the actual loss exceeds the disclosed var whereas the expected number of exceptions with a 99 var is 74 for each sample bank we extract from historical vars a risk overstatement coefficient ranging between 19 and 79 we attribute var overstatement to several factors including extreme cautiousness and underestimation of diversification effects when aggregating vars across business lines and or risk categories we also discuss the economic and social cost of reporting inflated vars

macroeconomics and the term structure this paper provides an overview of the analysis of the term structure of interest rates with a special emphasis on recent developments at the intersection of macroeconomics and finance the topic is important to investors and also to policymakers who wish to extract macroeconomic expectations from longer term interest rates and take actions to influence those rates the simplest model of the term structure is the expectations hypothesis which posits that long term interest rates are expectations of future aver age short term rates in this paper we show that many features of the configuration of interest rates are puzzling from the perspective of the expectations hypothesis we review models that explain these anomalies using time varying risk premia although the quest for the fundamental macroeconomic explanations of these risk premia is ongoing inflation uncertainty seems to play a large role finally while modern finance theory prices bonds and other assets in a single unified framework we also consider an earlier approach based on segmented markets market segmentation seems important to understand the term structure of interest rates during the recent financial crisis jel e31 e43 e52 e58

roughing it up including jump components in the measurement modeling and forecasting of return volatility a rapidly growing literature has documented important improvements in financial return volatility measurement and forecasting via use of realized variation measures constructed from high frequency returns coupled with simple modeling procedures building on recent theoretical results in barndorff nielsen and shephard 2004a 2005 for related bi power variation measures the present paper provides a practical and robust framework for non parametrically measuring the jump component in asset return volatility in an application to the dm exchange rate the s p500 market index and the 30 year u s treasury bond yield we find that jumps are both highly prevalent and distinctly less persistent than the continuous sample path variation process moreover many jumps appear directly associated with specific macroeconomic news announcements separating jump from non jump movements in a simple but sophisticated volatility forecasting model we find that almost all of the predictability in daily weekly and monthly return volatilities comes from the non jump component our results thus set the stage for a number of interesting future econometric developments and important financial applications by separately modeling forecasting and pricing the continuous and jump components of the total return variation process

error correction mechanisms the interface between economic theory and applied econometrics is often one of uneasy compromise with the pragmatic justification for many accepted procedures resting on a theoretical base this paper examines the surprisingly strong arguments that exist in terms of economic theory for the use of error correction mechanisms in the specification of short run dynamic adjustment a common heresy exists that while economic theory provides a detailed analysis of comparative static equilibria it can offer no guidance as to the appropriate specification of dynamic adjustment towards an equilibrium perhaps in consequence it is not uncommon to find examples where the necessary dynamic specification is achieved by tacking onto an existing equilibrium specification some relatively ad hoc short run adjustment scheme the intercession of stochastic arguments in this process is confused and critical implications are frequently ignored in practice but perhaps more importantly there will typically be no guarantee that the dynamic specification is consistent with the prescribed equilibrium consistency in this sense requires that the short run dynamic adjustment be directed by the perceived disequilibrium and that eventual convergence to the equilibrium position be ensured that two separate theoretical arguments co exist within the final specification is the root cause of many difficulties both theoretical and empirical this abstract was borrowed from another version of this item

electoral cycles and budgetary growth in veterans benefit programs while many studies have generated negative findings regarding the general existence of electoral cycles in economic phenomena we have found an apparently robust electoral cycle in veterans benefits this pattern was found between 1961 and 1978 but has disappeared since then we use this case to investigate the possibility that electoral cycles might contribute to the growth of government spending using two different methods of inference we find no strong basis to conclude that such cycles cause increasing public sector growth

time series copulas for heteroskedastic data we propose parametric copulas that capture serial dependence in stationary heteroskedastic time series we suggest copulas for first order markov series and then extend them to higher orders and multivariate series we derive the copula of a volatility proxy based on which we propose new measures of volatility dependence including co movement and spillover in multivariate series in general these depend upon the marginal distributions of the series using exchange rate returns we show that the resulting copula models can capture their marginal distributions more accurately than univariate and multivariate generalized autoregressive conditional heteroskedasticity models and produce more accurate value at risk forecasts

unconventional energy taxation and interstate welfare an analysis of pennsylvania s severance tax policy abstract natural gas production from unconventional sources has increased over the past decade a significant portion of this increase has come from output in the marcellus region of pennsylvania this output has altered gas markets and repositioned pennsylvania as a major gas exporter it has also put pennsylvania at odds with other states as it is one of a few without a formal severance tax on extractive resources in this paper we combine results from a structural demand model with a two sector trade model to analyze the interstate welfare impacts of pennsylvania s current severance tax proposal our results demonstrate that most of the welfare losses from this proposed policy are likely to be shifted to residents in other states we also demonstrate how fluctuations in gas prices can substantially reduce tax revenue these findings have important implications for both pennsylvania and u s energy policy given the significant rise in energy production from new sources throughout the u s

the great moderation of the term structure of uk interest rates abstract the conduct of monetary policy the term structure of interest rates and the structure of the economy in the uk have changed over the post wwii period we model the interaction between the macroeconomy and financial markets using a time varying var augmented with the factors from the yield curve there is evidence of a great moderation in the dynamics of the yield curve with the factors being persistent and volatile before the introduction of inflation targeting in 1992 but becoming stable afterwards the introduction of time variation in the factor augmented var improves the fit of the model and results in expectation hypothesis consistent yields that are close to actual yields even at long maturities monetary policy shocks had a significant impact on the volatility of inflation output and the policy rate over the pre inflation targeting era but their contribution has been negligible under the current regime shocks to the level of the yield curve accounted for a large fraction of inflation variability only before 1992

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

multivariate density forecast evaluation and calibration in financial risk management high frequency returns on foreign exchange we provide a framework for evaluating and improving multivariate density forecasts among other things the multivariate framework lets us evaluate the adequacy of density forecasts involving cross variable interactions such as time varying conditional correlations we also provide conditions under which a technique of density forecast calibration can be used to improve deficient density forecasts and we show how the calibration method can be used to generate good density forecasts from econometric models even when the conditional density is unknown finally motivated by recent advances in financial risk management we provide a detailed application to multivariate high frequency exchange rate density forecasts

continuous cascade models for asset returns abstract in this paper we make a short overview of continuous cascade models recently introduced to model asset return fluctuations we show that these models account in a very parcimonious manner for most of stylized facts of financial time series we review in more details the simplest continuous cascade namely the log normal multifractal random walk mrw it can simply be considered as a stochastic volatility model where the log volatility memory has a peculiar logarithmic shape this model possesses some appealing stability properties with respect to time aggregation we describe how one can estimate it using a gmm method and we present some applications to volatility and var value at risk forecasting

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

presidential politics budget deficits and monetary policy in the united states 1960 1976 this paper has focused on the extent to which the traditional tools of macroeconomic management in the united states monetary and fiscal policy have contributed to a political business cycle regardless of whether politicians can successfully influence real economic variables to their own ends the evidence presented here suggests that they tried and that they enjoyed some at least indirect aid from their independent monetary authorities in doing so several major conclusions emerge

capturing deep tail risk via sequential learning of quantile dynamics abstract this paper develops a conditional quantile model that can learn long term and short term memories of sequential data it builds on sequential neural networks and yet outputs interpretable dynamics we apply the model to asset return time series across eleven asset classes using historical data from the 1960s to 2018 our results reveal that it extracts not only the serial dependence structure in conditional volatility but also the memories buried deep in the tails of historical prices we further evaluate its value at risk forecasts against a wide range of prevailing models our model outperforms the garch family as well as models using filtered historical simulation conditional extreme value theory and dynamic quantile regression these studies indicate that conditional quantiles of asset return have persistent sources of risk that are not coming from those responsible for volatility clustering these findings could have important implications for risk management in general and tail risk forecasts in particular

fiscal constraints and electoral manipulation in american social welfare a merican social welfare policy involves a politically significant fiscal interaction between short run pay as you go constraints and long run equilibrium constraints motivated by the contributory principle and the concept of actuarial soundness the fiscal constraints induce conflict between benefit recipients and payroll tax payers to support small election year reductions in payroll taxes means tested program benefits are slightly reduced in election years compared to non election year levels under similar economic conditions the existence of the constraints and of the election year changes is tested using a multivariate time series regression model of monthly transfer payments and contributions for social insurance during years 1948 87 short run dynamics arefound to be weakly incrementalist but otherwise the results support the argument extraordinary manipulations are identified during 1972 special technical features of the econometric analysis are a nonlinear dynamic specification robust generalized method of moments estimation and near cointegration

economic adversity and voter turnout does economic adversity affect whether people vote data from the november 1974 current population survey are used to estimate the effect that unemployment poverty and a decline in financial well being have on voter turnout each economic problem suppresses participation these individual level findings are corroborated with aggregate time series data from presidential and midterm elections since 1896 when a person suffers economic adversity his scarce resources are spent holding body and soul together not on remote concerns like politics economic problems both increase the opportunity costs of political participation and reduce a person s capacity to attend to politics

price pressure in the government bond market what determines the term structure of interest rates standard economic theory links the interest rate for maturity t to the willingness of a representative agent to substitute consumption between times 0 and t the standard model contrasts sharply with a more informal view based on investors preferred habitat proposed by john culbertson 1957 and franco modigliani and richard sutch 1966 according to the preferred habitat view there are investor clienteles with preferences for specific maturities and the interest rate for a given maturity is influenced by the demand of the corresponding clientele and the supply of bonds with that maturity for example the typical clientele for long term bonds are pension funds an increase in their demand would be expected to raise prices of long term bonds and thus lower long term interest rates in short preferred habitat implies that there is price pressure in the bond market while the preferred habitat view has intuitive appeal it has not entered into the academic mainstream typically being relegated to a paragraph in mba level textbooks one reason for this is the mixed findings in early empirical studies of the term structure specifically between 1962 and 1964 the us treasury and federal reserve raised the supply of short term government debt while simultaneously lowering the supply of long term debt this program known as operation twist aimed to raise shortterm interest rates and so improve the balance of payments while also lowering long term rates to stimulate private investment a number of papers evaluated operation twist and while they reached different conclusions none found strong evidence that the operation was effective in flattening the term structure e g modigliani price pressure in the government bond market

a hybrid spline based parametric model for the yield curve empirical evidence indicates that both nominal and real yield curves in important markets have segmentation between their short end and their longer maturity segments this segmentation might affect term structure estimation introducing distortions in longer maturity yields especially in parametric models in order to deal with such segmentation we propose a new model that combines the flexibility of spline functions with the parsimoniousness of a parametric four factor exponential model the short end of the yield curve is fitted using a b spline function while longer segments are captured by the parametric model we illustrate the benefits of the proposed model for pricing and risk management purposes using two examples the real yield curve in the brazilian government index linked bond market and the us treasury nominal yield curve we show that in both markets our model is simultaneously able to fit the yield curve well and to provide unbiased value at risk estimates for all tested portfolios of bonds outperforming an important parametric benchmark model frequently adopted by central banks

the welfare analysis of a free trade zone intermediate goods and the asian tigers we analyse trade reform among the asean countries which recently began removing all mutual trade barriers the standard method to avoid complete specialisation in traded goods is to distinguish goods both by physical type and place of origin the so called armington assumption this methodology is not suitable for the sort of intermediate goods produced by the asean countries we develop a computational approach in the context of a non armington dynamic general equilibrium model analysing the results of a calibrated version of the model we find that trade liberalisation is generally welfare improving for the asean countries

bond yields and the federal reserve bond yields respond to policy decisions by the federal reserve and vice versa to learn about these responses i model a high frequency policy rule based on yield curve information and an arbitrage free bond market in continuous time the fed s target is a pure jump process jump intensities depend on the state of the economy and the meeting calendar of the federal open market committee the model has closed form solutions for yields as functions of a few state variables introducing monetary policy helps to match the whole yield curve because the target is an observable state variable that pins down its short end and introduces important seasonalities around fomc meetings the volatility of yields is snake shaped which the model explains with policy inertia the policy rule crucially depends on the two year yield and describes fed policy better than taylor rules

unequal participation democracy s unresolved dilemma presidential address american political science association 1996 low voter turnout is a serious democratic problem for five reasons 1 it means unequal turnout that is systematically biased against less well to do citizens 2 unequal turnout spells unequal political influence 3 u s voter turnout is especially low but measured as percent of voting age population it is also relatively low in most other countries 4 turnout in midterm regional local and supranational elections less salient but by no means unimportant elections tends to be especially poor 5 turnout appears to be declining everywhere the problem of inequality can be solved by institutional mechanisms that maximize turnout one option is the combination of voter friendly registration rules proportional representation infrequent elections weekend voting and holding less salient elections concurrently with the most important national elections the other option which can maximize turnout by itself is compulsory voting its advantages far outweigh the normative and practical objections to it

policy motivation and party differences in a dynamic spatial model of party competition we present a model of party competition that produces more realistic patterns of results than those often emphasized in the literature reversing downs 1957 we assume that parties win elections in order to formulate policies rather than formulate policies in order to win elections voters are modeled first as having perfect information about candidate positions and then under conditions of uncertainty in simulation experiments we show that policy motivation and voter uncertainty can bring about persistent and predictable party differences in sequential majority rule elections as the degree of voter certainty decreases parties diverge towards their optima whereas increases in voter certainty draw parties towards cycles in which party positions vary but predictable issue stances are maintained on the average

explorations into factors explaining money market returns in this article we measure and interpret the common factors that describe money market returns results are presented for both three and four factor models we find that the three factor model explains on average 86 percent of the total variation in most money market returns while the four factor model explains on average 90 percent of this variation using mimicking portfolios we provide an interpretation of the systematic risks represented by these factors in this article we attempt to measure and interpret the common factors that describe money market returns the factor approach we employ assumes that the covariance matrix of a set of random variables in this case excess returns can be decomposed into common or systematic components and idiosyncratic or nonsystematic components this decomposition into systematic and nonsystematic components is based on an assumption of a linear relationship between the returns of each security and a set of common factors this is the assumption of linear return generating models which form an integral part of the structure of many asset pricing theories for example arbitrage pricing theory apt as developed by ross 1976 the interpretation is that the common factors represent sources of systematic or nondiversifiable risk and the idiosyncratic component of returns represents diversifiable risks our focus here is not on testing a particular asset pricing model per se but on developing empirical evidence for the existence of stylized facts regarding money market returns the stylized facts take the form of the existence measurement and interpretation of the common factors that are found in money markets our attempt to measure and interpret these sources of systematic risk may eventually lead to the construction of observable eco

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

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