Application of the Bernhardt, Campello and Kutsoati (2006) test of herding to the calendar-year annual output growth and inflation forecasts suggests forecasters tend to exaggerate their differences, except at the shortest horizon when they tend to herd. We consider whether these types of behaviour can help to explain the puzzle that professional forecasters sometimes make point predictions and histogram forecasts which are mutually inconsistent.
{"title":"Do US Macroeconomic Forecasters Exaggerate Their Differences?","authors":"Michael P. Clements","doi":"10.2139/SSRN.2496433","DOIUrl":"https://doi.org/10.2139/SSRN.2496433","url":null,"abstract":"Application of the Bernhardt, Campello and Kutsoati (2006) test of herding to the calendar-year annual output growth and inflation forecasts suggests forecasters tend to exaggerate their differences, except at the shortest horizon when they tend to herd. We consider whether these types of behaviour can help to explain the puzzle that professional forecasters sometimes make point predictions and histogram forecasts which are mutually inconsistent.","PeriodicalId":425229,"journal":{"name":"ERN: Hypothesis Testing (Topic)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122513493","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}
We consider the problem of inference on a regression function at a point when the entire function satisfies a sign or shape restriction under the null. We propose a test that achieves the optimal minimax rate adaptively over a range of Holder classes, up to a log log n term, which we show to be necessary for adaptation. We apply the results to adaptive one-sided tests for the regression discontinuity parameter under a monotonicity restriction, the value of a monotone regression function at the boundary, and the proportion of true null hypotheses in a multiple testing problem.
{"title":"Adaptive Testing on a Regression Function at a Point","authors":"Timothy B. Armstrong","doi":"10.1214/15-AOS1342","DOIUrl":"https://doi.org/10.1214/15-AOS1342","url":null,"abstract":"We consider the problem of inference on a regression function at a point when the entire function satisfies a sign or shape restriction under the null. We propose a test that achieves the optimal minimax rate adaptively over a range of Holder classes, up to a log log n term, which we show to be necessary for adaptation. We apply the results to adaptive one-sided tests for the regression discontinuity parameter under a monotonicity restriction, the value of a monotone regression function at the boundary, and the proportion of true null hypotheses in a multiple testing problem.","PeriodicalId":425229,"journal":{"name":"ERN: Hypothesis Testing (Topic)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128574028","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 proposes a panel unit root test for micropanels with short time dimension (T) and large cross section (N). There are several distinctive features of this test. First, the test is based on a panel AR(1) model, which allows for cross-sectional dependency, which is introduced by the initial condition's assumption of a factor structure. Second, the test employs the panel AR(1) model with heterogeneous AR(1) coefficients. Third, the test does not use the AR(1) coefficient estimator. The effectiveness of the test rests on the fact that the initial condition has permanent effects on the trajectory of a time series in the presence of a unit root. To measure the effects of the initial condition, this paper employs cross-sectional regression using the first time series observations as a regressor and the last as a dependent variable. If there is a unit root in every individual time series, the coefficient of the regressor is equal to one. The t-ratio for the coefficient is this paper's test statistic and has a standard normal distribution in the limit. The t-ratio is based on the instrumental variables estimator that uses a reshuffled regressor as an instrument. The test proposed in this paper makes it possible to test for a unit root even at T=2 as long as N is large. Simulation results show that the test has reasonable empirical size and power. The test is applied to college graduates' monthly real wage in South Korea. The number of time series observations for this data is only two. The test rejects the null hypothesis of a unit root.
{"title":"Unit Root Tests for Dependent and Heterogeneous Micropanels","authors":"In Choi","doi":"10.2139/ssrn.2475810","DOIUrl":"https://doi.org/10.2139/ssrn.2475810","url":null,"abstract":"This paper proposes a panel unit root test for micropanels with short time dimension (T) and large cross section (N). There are several distinctive features of this test. First, the test is based on a panel AR(1) model, which allows for cross-sectional dependency, which is introduced by the initial condition's assumption of a factor structure. Second, the test employs the panel AR(1) model with heterogeneous AR(1) coefficients. Third, the test does not use the AR(1) coefficient estimator. The effectiveness of the test rests on the fact that the initial condition has permanent effects on the trajectory of a time series in the presence of a unit root. To measure the effects of the initial condition, this paper employs cross-sectional regression using the first time series observations as a regressor and the last as a dependent variable. If there is a unit root in every individual time series, the coefficient of the regressor is equal to one. The t-ratio for the coefficient is this paper's test statistic and has a standard normal distribution in the limit. The t-ratio is based on the instrumental variables estimator that uses a reshuffled regressor as an instrument. The test proposed in this paper makes it possible to test for a unit root even at T=2 as long as N is large. Simulation results show that the test has reasonable empirical size and power. The test is applied to college graduates' monthly real wage in South Korea. The number of time series observations for this data is only two. The test rejects the null hypothesis of a unit root.","PeriodicalId":425229,"journal":{"name":"ERN: Hypothesis Testing (Topic)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133474350","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}
Type-I and type-II errors effects do matter both from the rules enforcement perspective and vertically upward to rules enactment. The paper support conventional idea about detrimental influence on deterrence of both types of errors. At the same time special role of type-I errors is demonstrated based on strategic interaction between economic exchange participants supported by third-party enforcement with opportunities to discriminate players. The paper highlights the issue that errors in enforcement is not whole story: the simple classification of cases is suggested from the perspective of type-I and type-II errors in rules enforcement and rules enactment.
{"title":"Effects of the Third Party Errors","authors":"A. Shastitko","doi":"10.2139/ssrn.2529026","DOIUrl":"https://doi.org/10.2139/ssrn.2529026","url":null,"abstract":"Type-I and type-II errors effects do matter both from the rules enforcement perspective and vertically upward to rules enactment. The paper support conventional idea about detrimental influence on deterrence of both types of errors. At the same time special role of type-I errors is demonstrated based on strategic interaction between economic exchange participants supported by third-party enforcement with opportunities to discriminate players. The paper highlights the issue that errors in enforcement is not whole story: the simple classification of cases is suggested from the perspective of type-I and type-II errors in rules enforcement and rules enactment.","PeriodicalId":425229,"journal":{"name":"ERN: Hypothesis Testing (Topic)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132665247","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}
A procedure is developed to test whether conditional variances are constant over time in the context of generalized autoregressive conditional heteroscedasticity (GARCH) models with possible GARCH-in-mean effects. The approach is based on the quasilikelihood function, leaving the true distribution of model disturbances parametrically unspecified. The presence of possible nuisance parameters in the conditional mean is dealt with by using a pivotal bound and Monte Carlo resampling techniques to obtain a level-exact test procedure. Simulation experiments reveal that the permutation-based, quasilikelihood ratio test has very attractive power properties in comparison with omnibus Lagrange multiplier tests. An empirical application of the new procedure finds overwhelming evidence of GARCH effects in Fama-French portfolio returns, even when conditioning on the market risk factor.
{"title":"Testing for GARCH Effects with Quasilikelihood Ratios","authors":"Richard Luger","doi":"10.21314/JOR.2014.286","DOIUrl":"https://doi.org/10.21314/JOR.2014.286","url":null,"abstract":"A procedure is developed to test whether conditional variances are constant over time in the context of generalized autoregressive conditional heteroscedasticity (GARCH) models with possible GARCH-in-mean effects. The approach is based on the quasilikelihood function, leaving the true distribution of model disturbances parametrically unspecified. The presence of possible nuisance parameters in the conditional mean is dealt with by using a pivotal bound and Monte Carlo resampling techniques to obtain a level-exact test procedure. Simulation experiments reveal that the permutation-based, quasilikelihood ratio test has very attractive power properties in comparison with omnibus Lagrange multiplier tests. An empirical application of the new procedure finds overwhelming evidence of GARCH effects in Fama-French portfolio returns, even when conditioning on the market risk factor.","PeriodicalId":425229,"journal":{"name":"ERN: Hypothesis Testing (Topic)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127856184","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}
Microeconomic data often have within-cluster dependence. This dependence affects standard error estimation and inference in regression models, including the instrumental variables model. Standard corrections assume that the number of clusters is large, but when this is not the case, Wald and weak-instrument-robust tests can be severely over-sized. We examine the use of bootstrap methods to construct appropriate critical values for these tests when the number of clusters is small. We find that variants of the wild bootstrap perform well and reduce absolute size bias significantly, independent of instrument strength or cluster size. We also provide guidance in the choice among possible weak-instrument-robust tests when data have cluster dependence. These results are applicable to fixed-effects panel data models.
{"title":"Bootstrap Methods for Inference with Cluster Sample IV Models","authors":"K. Finlay, L. Magnusson","doi":"10.2139/ssrn.2574521","DOIUrl":"https://doi.org/10.2139/ssrn.2574521","url":null,"abstract":"Microeconomic data often have within-cluster dependence. This dependence affects standard error estimation and inference in regression models, including the instrumental variables model. Standard corrections assume that the number of clusters is large, but when this is not the case, Wald and weak-instrument-robust tests can be severely over-sized. We examine the use of bootstrap methods to construct appropriate critical values for these tests when the number of clusters is small. We find that variants of the wild bootstrap perform well and reduce absolute size bias significantly, independent of instrument strength or cluster size. We also provide guidance in the choice among possible weak-instrument-robust tests when data have cluster dependence. These results are applicable to fixed-effects panel data models.","PeriodicalId":425229,"journal":{"name":"ERN: Hypothesis Testing (Topic)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131210158","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}
Francesco Calvori, Drew D. Creal, S. J. Koopman, A. Lucas
We develop a new parameter stability test against the alternative of observation driven generalized autoregressive score dynamics. The new test generalizes the ARCH-LM test of Engle (1982) to settings beyond time-varying volatility and exploits any autocorrelation in the likelihood scores under the alternative. We compare the test's performance with that of alternative tests developed for competing time-varying parameter frameworks, such as structural breaks and observation driven parameter dynamics. The new test has higher and more stable power against alternatives with frequent regime switches or with non-local parameter driven time-variation. For parameter driven time variation close to the null or for infrequent structural changes, the test of Muller and Petalas (2010) performs best overall. We apply all tests empirically to a panel of losses given default over the period 1982--2010 and find significant evidence of parameter variation in the underlying beta distribution.
{"title":"Testing for Parameter Instability in Competing Modeling Frameworks","authors":"Francesco Calvori, Drew D. Creal, S. J. Koopman, A. Lucas","doi":"10.2139/ssrn.2379997","DOIUrl":"https://doi.org/10.2139/ssrn.2379997","url":null,"abstract":"We develop a new parameter stability test against the alternative of observation driven generalized autoregressive score dynamics. The new test generalizes the ARCH-LM test of Engle (1982) to settings beyond time-varying volatility and exploits any autocorrelation in the likelihood scores under the alternative. We compare the test's performance with that of alternative tests developed for competing time-varying parameter frameworks, such as structural breaks and observation driven parameter dynamics. The new test has higher and more stable power against alternatives with frequent regime switches or with non-local parameter driven time-variation. For parameter driven time variation close to the null or for infrequent structural changes, the test of Muller and Petalas (2010) performs best overall. We apply all tests empirically to a panel of losses given default over the period 1982--2010 and find significant evidence of parameter variation in the underlying beta distribution.","PeriodicalId":425229,"journal":{"name":"ERN: Hypothesis Testing (Topic)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121782481","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}
Long-horizon predictability is not a myth. We propose a new analytical standard error for predictive regressions that does not impose the null hypothesis that returns are unpredictable and exhibits substantial power gains relative to popular tests. Deriving the covariance matrix under the alternative hypothesis produces two new terms capturing the volatility of shocks to the regressor and their correlation with shocks to the prediction equation. Empirically, we show that failure to detect long-horizon predictability comes from lower power in tests derived under the null hypothesis. For many predictors, giving the alternative a chance allows short-run predictability to survive at long-horizons.
{"title":"Return Predictability Under the Alternative","authors":"Marco Rossi, Timothy T. Simin, Daniel R. Smith","doi":"10.2139/ssrn.2136047","DOIUrl":"https://doi.org/10.2139/ssrn.2136047","url":null,"abstract":"Long-horizon predictability is not a myth. We propose a new analytical standard error for predictive regressions that does not impose the null hypothesis that returns are unpredictable and exhibits substantial power gains relative to popular tests. Deriving the covariance matrix under the alternative hypothesis produces two new terms capturing the volatility of shocks to the regressor and their correlation with shocks to the prediction equation. Empirically, we show that failure to detect long-horizon predictability comes from lower power in tests derived under the null hypothesis. For many predictors, giving the alternative a chance allows short-run predictability to survive at long-horizons.","PeriodicalId":425229,"journal":{"name":"ERN: Hypothesis Testing (Topic)","volume":"462 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114002038","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 propose tests based on GLS-detrending for testing the null hypothesis of deterministic seasonality. Unlike existing tests for deterministic seasonality, our tests do not suffer from asymptotic size distortions under near integration. We also investigate the behavior of the proposed tests when the initial condition is not asymptotically negligible.
{"title":"On GLS -- Detrending for Deterministic Seasonality Testing","authors":"A. Skrobotov","doi":"10.2139/ssrn.2356868","DOIUrl":"https://doi.org/10.2139/ssrn.2356868","url":null,"abstract":"In this paper we propose tests based on GLS-detrending for testing the null hypothesis of deterministic seasonality. Unlike existing tests for deterministic seasonality, our tests do not suffer from asymptotic size distortions under near integration. We also investigate the behavior of the proposed tests when the initial condition is not asymptotically negligible.","PeriodicalId":425229,"journal":{"name":"ERN: Hypothesis Testing (Topic)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127865920","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 primary purpose of this paper is to test the hypothesis of capital mobility reduction in the wake of the global financial crisis of 2008-2009. Through the constructed models we tested hypotheses about the long- and short-term mobility of global capital by estimating the correlation between savings and investment rates. The paper also deals with the question of capital mobility in Russia. Recommendations on monetary policy in Russia in the coming years based on the obtained findings were made.
{"title":"The Feldstein-Horioka Puzzle: Modern Aspects","authors":"P. Trunin, A. Zubarev","doi":"10.2139/ssrn.2353911","DOIUrl":"https://doi.org/10.2139/ssrn.2353911","url":null,"abstract":"The primary purpose of this paper is to test the hypothesis of capital mobility reduction in the wake of the global financial crisis of 2008-2009. Through the constructed models we tested hypotheses about the long- and short-term mobility of global capital by estimating the correlation between savings and investment rates. The paper also deals with the question of capital mobility in Russia. Recommendations on monetary policy in Russia in the coming years based on the obtained findings were made.","PeriodicalId":425229,"journal":{"name":"ERN: Hypothesis Testing (Topic)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127166981","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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