This paper introduces identification-robust subvector tests and confidence sets (CS’s) that have asymptotic size equal to their nominal size and are asymptotically efficient under strong identification. Hence, inference is as good asymptotically as standard methods under standard regularity conditions, but also is identification robust. The results do not require special structure on the models under consideration, or strong identification of the nuisance parameters, as many existing methods do. We provide general results under high-level conditions that can be applied to moment condition, likelihood, and minimum distance models, among others. We verify these conditions under primitive conditions for moment condition models. In another paper, we do so for likelihood models. The results build on the approach of Chaudhuri and Zivot (2011), who introduce a C(a)-type Lagrange multiplier test and employ it in a Bonferroni subvector test. Here we consider two-step tests and CS’s that employ a C(a)-type test in the second step. The two-step tests are closely related to Bonferroni tests, but are not asymptotically conservative and achieve asymptotic efficiency under strong identification
{"title":"Identification-Robust Subvector Inference","authors":"D. Andrews","doi":"10.2139/SSRN.3032675","DOIUrl":"https://doi.org/10.2139/SSRN.3032675","url":null,"abstract":"This paper introduces identification-robust subvector tests and confidence sets (CS’s) that have asymptotic size equal to their nominal size and are asymptotically efficient under strong identification. Hence, inference is as good asymptotically as standard methods under standard regularity conditions, but also is identification robust. The results do not require special structure on the models under consideration, or strong identification of the nuisance parameters, as many existing methods do. We provide general results under high-level conditions that can be applied to moment condition, likelihood, and minimum distance models, among others. We verify these conditions under primitive conditions for moment condition models. In another paper, we do so for likelihood models. The results build on the approach of Chaudhuri and Zivot (2011), who introduce a C(a)-type Lagrange multiplier test and employ it in a Bonferroni subvector test. Here we consider two-step tests and CS’s that employ a C(a)-type test in the second step. The two-step tests are closely related to Bonferroni tests, but are not asymptotically conservative and achieve asymptotic efficiency under strong identification","PeriodicalId":447882,"journal":{"name":"ERN: Model Evaluation & Selection (Topic)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134585287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Many postulated relations in finance imply that expected asset returns strictly increase in an underlying characteristic. To examine the validity of such a claim, one needs to take the entire range of the characteristic into account, as is done in the recent proposal of Patton and Timmermann (2010). But their test is only a test for the direction of monotonicity, since it requires the relation to be monotonic from the outset: either weakly decreasing under the null or strictly increasing under the alternative. When the relation is non-monotonic or weakly increasing, the test can break down and falsely ‘establish’ a strictly increasing relation with high probability. We offer some alternative tests that do not share this problem. The behavior of the various tests is illustrated via Monte Carlo studies. We also present empirical applications to real data.
{"title":"Testing for Monotonicity in Expected Asset Returns","authors":"Joseph P. Romano, Michael Wolf","doi":"10.2139/ssrn.1858761","DOIUrl":"https://doi.org/10.2139/ssrn.1858761","url":null,"abstract":"Many postulated relations in finance imply that expected asset returns strictly increase in an underlying characteristic. To examine the validity of such a claim, one needs to take the entire range of the characteristic into account, as is done in the recent proposal of Patton and Timmermann (2010). But their test is only a test for the direction of monotonicity, since it requires the relation to be monotonic from the outset: either weakly decreasing under the null or strictly increasing under the alternative. When the relation is non-monotonic or weakly increasing, the test can break down and falsely ‘establish’ a strictly increasing relation with high probability. We offer some alternative tests that do not share this problem. The behavior of the various tests is illustrated via Monte Carlo studies. We also present empirical applications to real data.","PeriodicalId":447882,"journal":{"name":"ERN: Model Evaluation & Selection (Topic)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123155976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The aim of this note is to investigate the relationship between Gini's Mean Difference (GMD), the mean absolute deviation (MAD), the least absolute deviation (LAD), and the absolute deviation from a given quantile (QUAD). The latter measures can all be interpreted as equivalents either to the GMD of a transformed distribution, or alternatively, to a between-group GMD (BGMD) measure, according to the particular partition of the data. As such they all possess properties of the GMD but each omits the intra-group variability – and, of course, they give rise to different regression techniques. It is argued that the loss of the intra-group information is too heavy a price to pay, and that the analyst using one of these techniques should justify the omission of the intra-group variability from the analysis.
{"title":"The Relationship between Gini's Mean Difference and the Absolute Deviation from a Quantile","authors":"S. Yitzhaki, P. Lambert","doi":"10.2139/ssrn.2048397","DOIUrl":"https://doi.org/10.2139/ssrn.2048397","url":null,"abstract":"The aim of this note is to investigate the relationship between Gini's Mean Difference (GMD), the mean absolute deviation (MAD), the least absolute deviation (LAD), and the absolute deviation from a given quantile (QUAD). The latter measures can all be interpreted as equivalents either to the GMD of a transformed distribution, or alternatively, to a between-group GMD (BGMD) measure, according to the particular partition of the data. As such they all possess properties of the GMD but each omits the intra-group variability – and, of course, they give rise to different regression techniques. It is argued that the loss of the intra-group information is too heavy a price to pay, and that the analyst using one of these techniques should justify the omission of the intra-group variability from the analysis.","PeriodicalId":447882,"journal":{"name":"ERN: Model Evaluation & Selection (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129702900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a general statistical framework for estimation, testing and comparison of asset pricing models using the unconstrained distance measure of Hansen and Jagannathan (1997). The limiting results cover both linear and nonlinear models that could be correctly specified or misspecified. We propose modified versions of the existing model selection tests and new pivotal specification and model comparison tests with improved finite-sample properties. In addition, we provide formal tests of multiple model comparison. The excellent size and power properties of the proposed tests are demonstrated using simulated data from linear and nonlinear asset pricing models.
{"title":"Chi-Squared Tests for Evaluation and Comparison of Asset Pricing Models","authors":"Nikolay Gospodinov, Raymond Kan, Cesare Robotti","doi":"10.2139/ssrn.1800685","DOIUrl":"https://doi.org/10.2139/ssrn.1800685","url":null,"abstract":"This paper presents a general statistical framework for estimation, testing and comparison of asset pricing models using the unconstrained distance measure of Hansen and Jagannathan (1997). The limiting results cover both linear and nonlinear models that could be correctly specified or misspecified. We propose modified versions of the existing model selection tests and new pivotal specification and model comparison tests with improved finite-sample properties. In addition, we provide formal tests of multiple model comparison. The excellent size and power properties of the proposed tests are demonstrated using simulated data from linear and nonlinear asset pricing models.","PeriodicalId":447882,"journal":{"name":"ERN: Model Evaluation & Selection (Topic)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128391553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-09-01DOI: 10.1111/j.1475-4991.2010.00409.x
Jochen Hartwig
Baumol's (1967) seminal model of structural change predicts that large service industries financed mainly through taxes and social contributions - like health care and education, for instance - will acquire ever-larger shares of total expenditures and that, concomitantly, overall productivity growth will decline. Applying a new testing strategy for Baumol's model, Nordhaus (2008) finds strong evidence in favor of the “cost and growth diseases” in U.S. GDP-by-industry data (published by the Department of Commerce's Bureau of Economic Analysis). The aim of the present paper is twofold. The first is to check whether Nordhaus's results can be reproduced using U.S. industry data from the EU KLEMS database. Second, Nordhaus's testing methodology is applied to European Union data from the same database. The results suggest that - although there are differences vis-a-vis the U.S. - the EU also shows symptoms of “Baumol's diseases.”
{"title":"Testing the Baumol–Nordhaus Model with EU KLEMS Data","authors":"Jochen Hartwig","doi":"10.1111/j.1475-4991.2010.00409.x","DOIUrl":"https://doi.org/10.1111/j.1475-4991.2010.00409.x","url":null,"abstract":"Baumol's (1967) seminal model of structural change predicts that large service industries financed mainly through taxes and social contributions - like health care and education, for instance - will acquire ever-larger shares of total expenditures and that, concomitantly, overall productivity growth will decline. Applying a new testing strategy for Baumol's model, Nordhaus (2008) finds strong evidence in favor of the “cost and growth diseases” in U.S. GDP-by-industry data (published by the Department of Commerce's Bureau of Economic Analysis). The aim of the present paper is twofold. The first is to check whether Nordhaus's results can be reproduced using U.S. industry data from the EU KLEMS database. Second, Nordhaus's testing methodology is applied to European Union data from the same database. The results suggest that - although there are differences vis-a-vis the U.S. - the EU also shows symptoms of “Baumol's diseases.”","PeriodicalId":447882,"journal":{"name":"ERN: Model Evaluation & Selection (Topic)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132172298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper we take the subject in the methods of business valuation. Starting with a brief introduction about the uncertainty evaluation, we review the operating lease, income-based method, mixed, ending with the empirical ones, highlighting the advantages and disadvantages of each.
{"title":"Methods of Business Valuation","authors":"A. Saravalle","doi":"10.2139/ssrn.2007521","DOIUrl":"https://doi.org/10.2139/ssrn.2007521","url":null,"abstract":"In this paper we take the subject in the methods of business valuation. Starting with a brief introduction about the uncertainty evaluation, we review the operating lease, income-based method, mixed, ending with the empirical ones, highlighting the advantages and disadvantages of each.","PeriodicalId":447882,"journal":{"name":"ERN: Model Evaluation & Selection (Topic)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115198739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
It is important to incorporate diverse heavy-tailed dependency between risks in estimating economic capital. Copulas can be a useful technique to capture dependence structure where extreme events occur simultaneously. Using the sample of U.S. property liability insurance industry, we examine the impact of different dependence structure between market risk and underwriting risk of insurance portfolio on the economic capital measured by Value-at-Risk (VaR) and Expected Shortfall (ES). We identify the type of copula that best fits the given application data and perform a goodness of fit test to assess the adequacy of the copula model selected. The results suggest that the grouped t copula is better performed than the standard t copula to describe the dependence structure in an insurance setting where different type of risk factors coexists. The result also shows the incremental diversification benefit in the joint modeling of underwriting risk and market risk compared to the modeling of market risk only considered, indicating that both risks diversify against one another to some degree.
{"title":"Measuring Economic Capital: Value-at-Risk, Expected Shortfall and Copula Approach","authors":"Jeungbo Shim, Seung-Hwan Lee, R. MacMinn","doi":"10.2139/ssrn.1840124","DOIUrl":"https://doi.org/10.2139/ssrn.1840124","url":null,"abstract":"It is important to incorporate diverse heavy-tailed dependency between risks in estimating economic capital. Copulas can be a useful technique to capture dependence structure where extreme events occur simultaneously. Using the sample of U.S. property liability insurance industry, we examine the impact of different dependence structure between market risk and underwriting risk of insurance portfolio on the economic capital measured by Value-at-Risk (VaR) and Expected Shortfall (ES). We identify the type of copula that best fits the given application data and perform a goodness of fit test to assess the adequacy of the copula model selected. The results suggest that the grouped t copula is better performed than the standard t copula to describe the dependence structure in an insurance setting where different type of risk factors coexists. The result also shows the incremental diversification benefit in the joint modeling of underwriting risk and market risk compared to the modeling of market risk only considered, indicating that both risks diversify against one another to some degree.","PeriodicalId":447882,"journal":{"name":"ERN: Model Evaluation & Selection (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129889259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-03-01DOI: 10.5089/9781455220977.001
L. Zeng
This paper develops a new forecasting framework for GDP growth in Korea to complement and further enhance existing forecasting approaches. First, a range of forecast models, including indicator- and pure time-series models, are evaluated for their forecasting performance. Based on the evaluation results, a new forecasting framework is developed for GDP projections. The framework also generates a data-driven reference band for the projections, and is therefore convenient to update. The framework is applied to the current World Economic Outlook (WEO) forecast period and the Great Recession to compare its performance to past projections. Results show that the performance of the new framework often improves the forecasts, especially at quarterly frequency, and the forecasting exercise will be better informed by cross-checking with the new data-driven framework projections.
{"title":"Evaluating GDP Forecasting Models for Korea","authors":"L. Zeng","doi":"10.5089/9781455220977.001","DOIUrl":"https://doi.org/10.5089/9781455220977.001","url":null,"abstract":"This paper develops a new forecasting framework for GDP growth in Korea to complement and further enhance existing forecasting approaches. First, a range of forecast models, including indicator- and pure time-series models, are evaluated for their forecasting performance. Based on the evaluation results, a new forecasting framework is developed for GDP projections. The framework also generates a data-driven reference band for the projections, and is therefore convenient to update. The framework is applied to the current World Economic Outlook (WEO) forecast period and the Great Recession to compare its performance to past projections. Results show that the performance of the new framework often improves the forecasts, especially at quarterly frequency, and the forecasting exercise will be better informed by cross-checking with the new data-driven framework projections.","PeriodicalId":447882,"journal":{"name":"ERN: Model Evaluation & Selection (Topic)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125152520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-02-25DOI: 10.1093/acprof:osobl/9780199594641.003.0014
D. Stark
This essay is the concluding chapter for The Worth of Goods: Valuation and Pricing in the Economy, edited by Patrik Aspers and Jens Beckert (Oxford University Press). I start with an insight of John Dewey's that the terms price, prize, and praise all share a common Latin root. To this triplicate I add a fourth, perform, using these four concepts as a device to discuss the papers in the volume. In one section, I address the phenomenon of Top Ten lists: On-line ratings and rankings by consumers now provide vast sources of data on prizing and appraising - new means to register value judgments in the economy.
{"title":"What's Valuable?","authors":"D. Stark","doi":"10.1093/acprof:osobl/9780199594641.003.0014","DOIUrl":"https://doi.org/10.1093/acprof:osobl/9780199594641.003.0014","url":null,"abstract":"This essay is the concluding chapter for The Worth of Goods: Valuation and Pricing in the Economy, edited by Patrik Aspers and Jens Beckert (Oxford University Press). I start with an insight of John Dewey's that the terms price, prize, and praise all share a common Latin root. To this triplicate I add a fourth, perform, using these four concepts as a device to discuss the papers in the volume. In one section, I address the phenomenon of Top Ten lists: On-line ratings and rankings by consumers now provide vast sources of data on prizing and appraising - new means to register value judgments in the economy.","PeriodicalId":447882,"journal":{"name":"ERN: Model Evaluation & Selection (Topic)","volume":"19 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131922850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
High frequency data is a recent entrant to the world of statistics as they relate to the markets. With tick by tick data we get to see the microstructure of the markets and often are better able to see how they vary from the traditional portrayal. Traditional tools used to look at daily and weekly volatilities are not often very useful in timescales of seconds and minutes. In this paper we try to look at two of the most highly traded stocks in the Indian stock market. The large and small errors tend to cluster together, and thus autoregressive conditional heteroscedasticity models are introduced. First we look at ARCH models on tick by tick data of SBI. Then we look at the GARCH models – with two stocks SBI and TATA – and its variants such as PGARCH and EGARCH to try to see if we can predict the conditional variance. We also glance at the DCC GARCH model to see if a bivariate view gives us any new insights. Finally we try to sum up the various techniques by evaluating them according to their utility in estimating high frequency data.
{"title":"Analysing High Frequency Data Using ARCH and GARCH Methods","authors":"R. Krishnan","doi":"10.2139/ssrn.1611531","DOIUrl":"https://doi.org/10.2139/ssrn.1611531","url":null,"abstract":"High frequency data is a recent entrant to the world of statistics as they relate to the markets. With tick by tick data we get to see the microstructure of the markets and often are better able to see how they vary from the traditional portrayal. Traditional tools used to look at daily and weekly volatilities are not often very useful in timescales of seconds and minutes. In this paper we try to look at two of the most highly traded stocks in the Indian stock market. The large and small errors tend to cluster together, and thus autoregressive conditional heteroscedasticity models are introduced. First we look at ARCH models on tick by tick data of SBI. Then we look at the GARCH models – with two stocks SBI and TATA – and its variants such as PGARCH and EGARCH to try to see if we can predict the conditional variance. We also glance at the DCC GARCH model to see if a bivariate view gives us any new insights. Finally we try to sum up the various techniques by evaluating them according to their utility in estimating high frequency data.","PeriodicalId":447882,"journal":{"name":"ERN: Model Evaluation & Selection (Topic)","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134328659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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