{"title":"Consistent Cell Means for Topcoded Incomes in the Public Use March CPS (1976-2007)","authors":"Jeff Larrimore, R. Burkhauser, S. Feng, L. Zayatz","doi":"10.3386/W13941","DOIUrl":"https://doi.org/10.3386/W13941","url":null,"abstract":"Using the internal March CPS, we create and in this paper distribute to the larger research community a cell mean series that provides the mean of all income values above the topcode for any income source of any individual in the public use March CPS that has been topcoded since 1976. We also describeour construction of this series. When we use this series together with the public use March CPS, we closely match the yearly mean income levels and income inequalities of the U.S. population found using the internal March CPS data.","PeriodicalId":418701,"journal":{"name":"ERN: Time-Series Models (Single) (Topic)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114261490","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}
{"title":"Do Small Businesses Create More Jobs? New Evidence from the National Establishment Time Series","authors":"D. Neumark, Brandon Wall, Junfu Zhang","doi":"10.3386/W13818","DOIUrl":"https://doi.org/10.3386/W13818","url":null,"abstract":"We use a new database, the National Establishment Time Series (NETS), to revisit the debate about the role of small businesses in job creation. Birch (e.g., 1987) argued that small firms are the most important source of job creation in the U.S. economy, but Davis et al. (1996a) argued that this conclusion was flawed, and based on improved methods and using data for the manufacturing sector they concluded that there was no relationship between establishment size and net job creation. Using the NETS data, we examine evidence for the overall economy, as well as for different sectors. The results indicate that small establishments and small firms create more jobs, on net, although the difference is much smaller than what is suggested by Birch's methods. However, the negative relationship between establishment size and job creation is much less clear for the manufacturing sector, which may explain some of the earlier findings contradicting Birch's conclusions.","PeriodicalId":418701,"journal":{"name":"ERN: Time-Series Models (Single) (Topic)","volume":"2 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129581058","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}
{"title":"Volatility Forecast Comparison Using Imperfect Volatility Proxies","authors":"Andrew J. Patton","doi":"10.2139/ssrn.932890","DOIUrl":"https://doi.org/10.2139/ssrn.932890","url":null,"abstract":"The use of a conditionally unbiased, but imperfect, volatility proxy can lead to undesirable outcomes in standard methods for comparing conditional variance forecasts. We derive necessary and sufficient conditions on functional form of the loss function for the ranking of competing volatility forecasts to be robust to the presence of noise in the volatility proxy, and derive some interesting special cases of this class of \"robust\" loss functions. We motivate the theory with analytical results on the distortions caused by some widely-used loss functions, when used with standard volatility proxies such as squared returns, the intra-daily range or realised volatility. The methods are illustrated with an application to the volatility of returns on IBM over the period 1993 to 2003.","PeriodicalId":418701,"journal":{"name":"ERN: Time-Series Models (Single) (Topic)","volume":"267 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122933209","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}
{"title":"Dynamic Effects of Fiscal Shocks Upon Diverse Macroeconomic Variables: A Structural VAR Analysis for Argentina","authors":"E. Rezk, M. C. Avramovich, Martín Basso","doi":"10.2139/SSRN.2005159","DOIUrl":"https://doi.org/10.2139/SSRN.2005159","url":null,"abstract":"The paper studies the dynamic effects of fiscal policy shocks upon Argentine macroeconomic variables such as the gross domestic product, the inflation rate and the level of unemployment; a structural Vector Autoregression model is resorted to in order to estimate the impulse response functions; the econometric analysis is carried out for the period 1984-2005 (second quarter) and quarterly logarithmic real variables are used for the VAR´s specification. Point estimation of impulse response functions indicate both a relatively low statistical significance of fiscal shocks upon macroeconomic variables and a short-lived impact of innovations while at the same time cast doubts upon some traditionally accepted Keynesian macroeconomic policy prescriptions.","PeriodicalId":418701,"journal":{"name":"ERN: Time-Series Models (Single) (Topic)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126785079","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}
{"title":"The Long Range Dependence Paradigm for Macroeconomics and Finance","authors":"Marc Henry, P. Zaffaroni","doi":"10.2139/ssrn.1084982","DOIUrl":"https://doi.org/10.2139/ssrn.1084982","url":null,"abstract":"The long range dependence paradigm appears to be a suitable description of the data generating process for many observed economic time series. This is mainly due to the fact that it naturally characterizes time series displaying a high degree of persistence, in the form of a long lasting effect of unanticipated shocks, yet exhibiting mean reversion. Whereas linear long range dependent time series models have been extensively used in macroeconomics, empirical evidence from financial time series prompted the development of nonlinear long range dependent time series models, in particular models of changing volatility. We discuss empirical evidence of long range dependence as well as the theoretical issues, both for economics and econometrics, such evidence has stimulated.","PeriodicalId":418701,"journal":{"name":"ERN: Time-Series Models (Single) (Topic)","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114876347","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}
{"title":"Certain Aspects of Generalized Box-Jenkins Models","authors":"Richard W. Hill","doi":"10.3386/w0082","DOIUrl":"https://doi.org/10.3386/w0082","url":null,"abstract":"We define a class of models that are generalizations of regression models and moving average-autoregressive time series models. Then we investigate the asymptotic and computational properties of the maximum likelihood estimator, with numerical examples. The main conclusion is that care must be exercised when using simple approximations to the covariance matrix of the estimates.","PeriodicalId":418701,"journal":{"name":"ERN: Time-Series Models (Single) (Topic)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1975-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115338296","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}