Research papers on time series econometrics

Does pay inequality within a team affect performance? Introduction The business of sports draws considerable attention from the media and the general public.

Research papers on time series econometrics

Research papers on time series econometrics

Time irreversible copula-based Markov models Joint with Brendan K. BeareEconometric Theory 30 5 Economic and financial time series frequently exhibit time irreversible dynamics. For instance, there is considerable evidence of asymmetric fluctuations in many macroeconomic and financial variables, and certain game theoretic models of price determination predict asymmetric cycles in price series.

In this paper we make two primary contributions to the econometric literature on time reversibility. First, we propose a new test of time reversibility, applicable to stationary Markov chains.

Compared to existing tests, our test has the advantage of being consistent against arbitrary violations of reversibility. Second, we explain how a circulation density function may be used to characterize the nature of time irreversibility when it is present. We propose a copula-based estimator of the circulation density, and verify that it is well behaved asymptotically under suitable regularity conditions.

We illustrate the use of our time reversibility test and circulation density estimator by applying them to five years of Canadian gasoline price markup data.

Vine copula specifications for stationary multivariate Markov chains Joint with Brendan K. Vine copulae provide a graphical framework in which multiple bivariate copulae may be combined in a consistent fashion to yield a more complex multivariate copula.

In this paper we discuss the use of vine copulae to build flexible semiparametric models for stationary multivariate higher-order Markov chains.

We propose a new vine structure, the M-vine, that is particularly well suited to this purpose. Stationarity may be imposed by requiring the equality of certain copulae in the M-vine, while the Markov property may be imposed by requiring certain copulae to be independence copulae.

Cointegrated linear processes in Hilbert space Joint with Brendan K. Our main result is a version of the Granger-Johansen representation theorem: We develop improved statistical procedures for testing the null hypothesis of stochastic monotonicity.

Stochastic monotonicity can be reformulated in terms of the concavity of cross-sections of a copula function; our test statistic is based on an empirical measure of departures from concavity.

While existing tests of stochastic monotonicity deliver a limiting rejection rate equal to the nominal significance level at one point and below the nominal significance level elsewhere in the null, our test raises the limiting rejection rate to the nominal significance level over a wide region of the null.

This improves power against relevant local alternatives. Implementation of our procedure is based on preliminary estimation of a contact set, similar to procedures developed recently in other contexts.

To show the validity of our approach we draw on recent results on the directional differentiability of the least concave majorant operator, and on bootstrap inference when smoothness conditions sufficient to apply the functional delta method for the bootstrap are not satisfied.

An application to intergenerational income mobility is provided. New nonparametric tests of copula exchangeability and radial symmetry are proposed. The novel aspect of the tests is a resampling procedure that exploits group invariance conditions associated with the relevant symmetry hypothesis.

They may be viewed as modified versions of randomization tests, the latter being inapplicable due to the unobservability of margins. Our tests are simple to compute, control size asymptotically, consistently detect arbitrary forms of asymmetry, and do not require the specification of a tuning parameter.

Simulations indicate excellent small sample properties compared to existing procedures involving the bootstrap. The critical values are obtained by a modified randomization procedure designed to exploit asymptotic group invariance conditions. Implementation of the test is intuitive and simple, and does not require any specification of a tuning parameter or weight function.Time Series, Time series Econometrics, Time-Series Analysis, Time series analysis Forecasting Realized Volatility Using A Nonnegative Semiparametric Model This Working Paper is brought to you for free and open access by the School of Economics at Institutional .

A warning for time series analysis - to find interesting results, you need variation in your data. For example, it would be difficult to find the effect of defense spending on American manufacturing industries if defense spending does not change much from year to year.

totic theory, Hamilton () and Kilian and Lütkepohl () for time-series methods, Wooldridge () for panel data and discrete response models, and Li and Racine () for nonparametrics and semiparametric econometrics. Twenty Years of Time Series Econometrics in Ten Pictures Author(s): James H.

Introductory Econometrics Additional Information In lieu of an abstract, here is a brief excerpt of the content: In the s and s there was a great spirit of optimism and confidence in econometrics.

Stock and Mark W. Watson This review tells the story of the past 20 years of time series econometrics are good surveys of the many developments in financial econometrics: for example, see the papers in Ait-Sahalia and Hansen ().

Another concerns the choice of. Thus the time series econometrics research agenda grounded in economics had to take a stand on how people inside economic models made forecasts.

2 The rational expectations approach pioneered by Muth (), Lucas (a,b) provided. Time Series Econometrics Academic Year: / 4th Term Instructor(s): João Valle e Azevedo Time Series in the Frequency Domain (time allowing) João Valle e Azevedo is an Economist at the Research Department of Banco de Portugal since , Head of Monetary Policy Division since , being also Invited.

Econ Time Series Econometrics