Search results

1 – 10 of 56
To view the access options for this content please click here
Book part
Publication date: 8 February 2006

Gary Koop and Simon Potter

Abstract

Details

Nonlinear Time Series Analysis of Business Cycles
Type: Book
ISBN: 978-0-44451-838-5

To view the access options for this content please click here
Book part
Publication date: 30 August 2019

Gary Koop and Luca Onorante

Many recent chapters have investigated whether data from internet search engines such as Google can help improve nowcasts or short-term forecasts of macroeconomic…

Abstract

Many recent chapters have investigated whether data from internet search engines such as Google can help improve nowcasts or short-term forecasts of macroeconomic variables. These chapters construct variables based on Google searches and use them as explanatory variables in regression models. We add to this literature by nowcasting using dynamic model selection (DMS) methods which allow for model switching between time-varying parameter regression models. This is potentially useful in an environment of coefficient instability and over-parameterization which can arise when forecasting with Google variables. We extend the DMS methodology by allowing for the model switching to be controlled by the Google variables through what we call “Google probabilities”: instead of using Google variables as regressors, we allow them to determine which nowcasting model should be used at each point in time. In an empirical exercise involving nine major monthly US macroeconomic variables, we find DMS methods to provide large improvements in nowcasting. Our use of Google model probabilities within DMS often performs better than conventional DMS methods.

Details

Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A
Type: Book
ISBN: 978-1-78973-241-2

Keywords

To view the access options for this content please click here
Book part
Publication date: 19 November 2014

Miguel Belmonte and Gary Koop

This paper investigates the usefulness of switching Gaussian state space models as a tool for implementing dynamic model selection (DMS) or averaging (DMA) in time-varying…

Abstract

This paper investigates the usefulness of switching Gaussian state space models as a tool for implementing dynamic model selection (DMS) or averaging (DMA) in time-varying parameter regression models. DMS methods allow for model switching, where a different model can be chosen at each point in time. Thus, they allow for the explanatory variables in the time-varying parameter regression model to change over time. DMA will carry out model averaging in a time-varying manner. We compare our exact method for implementing DMA/DMS to a popular existing procedure which relies on the use of forgetting factor approximations. In an application, we use DMS to select different predictors in an inflation forecasting application. We find strong evidence of model switching. We also compare different ways of implementing DMA/DMS and find forgetting factor approaches and approaches based on the switching Gaussian state space model to lead to similar results.

To view the access options for this content please click here
Book part
Publication date: 1 January 2008

Abstract

Details

Bayesian Econometrics
Type: Book
ISBN: 978-1-84855-308-8

To view the access options for this content please click here
Book part
Publication date: 1 January 2008

Siddhartha Chib, William Griffiths, Gary Koop and Dek Terrell

Bayesian Econometrics is a volume in the series Advances in Econometrics that illustrates the scope and diversity of modern Bayesian econometric applications, reviews some…

Abstract

Bayesian Econometrics is a volume in the series Advances in Econometrics that illustrates the scope and diversity of modern Bayesian econometric applications, reviews some recent advances in Bayesian econometrics, and highlights many of the characteristics of Bayesian inference and computations. This first paper in the volume is the Editors’ introduction in which we summarize the contributions of each of the papers.

Details

Bayesian Econometrics
Type: Book
ISBN: 978-1-84855-308-8

To view the access options for this content please click here
Book part
Publication date: 1 January 2008

Gary Koop, Roberto Leon-Gonzalez and Rodney Strachan

This paper develops methods of Bayesian inference in a cointegrating panel data model. This model involves each cross-sectional unit having a vector error correction…

Abstract

This paper develops methods of Bayesian inference in a cointegrating panel data model. This model involves each cross-sectional unit having a vector error correction representation. It is flexible in the sense that different cross-sectional units can have different cointegration ranks and cointegration spaces. Furthermore, the parameters that characterize short-run dynamics and deterministic components are allowed to vary over cross-sectional units. In addition to a noninformative prior, we introduce an informative prior which allows for information about the likely location of the cointegration space and about the degree of similarity in coefficients in different cross-sectional units. A collapsed Gibbs sampling algorithm is developed which allows for efficient posterior inference. Our methods are illustrated using real and artificial data.

Details

Bayesian Econometrics
Type: Book
ISBN: 978-1-84855-308-8

To view the access options for this content please click here
Book part
Publication date: 1 January 2008

Gary Koop

Equilibrium job search models allow for labor markets with homogeneous workers and firms to yield nondegenerate wage densities. However, the resulting wage densities do…

Abstract

Equilibrium job search models allow for labor markets with homogeneous workers and firms to yield nondegenerate wage densities. However, the resulting wage densities do not accord well with empirical regularities. Accordingly, many extensions to the basic equilibrium search model have been considered (e.g., heterogeneity in productivity, heterogeneity in the value of leisure, etc.). It is increasingly common to use nonparametric forms for these extensions and, hence, researchers can obtain a perfect fit (in a kernel smoothed sense) between theoretical and empirical wage densities. This makes it difficult to carry out model comparison of different model extensions. In this paper, we first develop Bayesian parametric and nonparametric methods which are comparable to the existing non-Bayesian literature. We then show how Bayesian methods can be used to compare various nonparametric equilibrium search models in a statistically rigorous sense.

Details

Bayesian Econometrics
Type: Book
ISBN: 978-1-84855-308-8

To view the access options for this content please click here
Book part
Publication date: 1 January 2008

Deborah Gefang

This paper proposes a Bayesian procedure to investigate the purchasing power parity (PPP) utilizing an exponential smooth transition vector error correction model (VECM)…

Abstract

This paper proposes a Bayesian procedure to investigate the purchasing power parity (PPP) utilizing an exponential smooth transition vector error correction model (VECM). Employing a simple Gibbs sampler, we jointly estimate the cointegrating relationship along with the nonlinearities caused by the departures from the long-run equilibrium. By allowing for nonlinear regime changes, we provide strong evidence that PPP holds between the US and each of the remaining G7 countries. The model we employed implies that the dynamics of the PPP deviations can be rather complex, which is attested to by the impulse response analysis.

Details

Bayesian Econometrics
Type: Book
ISBN: 978-1-84855-308-8

To view the access options for this content please click here
Book part
Publication date: 1 January 2008

Abstract

Details

Bayesian Econometrics
Type: Book
ISBN: 978-1-84855-308-8

To view the access options for this content please click here
Book part
Publication date: 1 January 2008

Nadine McCloud and Subal C. Kumbhakar

One of the foremost objectives of the Common Agricultural Policy (CAP) in the European Union (EU) is to increase agricultural productivity through subsidization of…

Abstract

One of the foremost objectives of the Common Agricultural Policy (CAP) in the European Union (EU) is to increase agricultural productivity through subsidization of farmers. However, little empirical research has been done to examine the effect of subsidies on farm performance and, in particular, the channels through which subsidies affect productivity. Using a Bayesian hierarchical model in which input productivity, efficiency change, and technical change depend on subsidies and other factors, including farm location, we analyze empirically how subsidies affect the performance of farms. We use an unbalanced panel from the EU's Farm Accountancy Data Network on Danish, Finnish, and Swedish dairy farms and partition the data into eight regions. The data set covers the period 1997–2003 and has a total of 6,609 observations. The results suggest that subsidies drive productivity through efficiency and input productivities and the magnitudes of these effects differ across regions. In contrast to existing studies, we find that subsidies have a positive impact on technical efficiency. The contribution of subsidies to output is largest for dairy farms in Denmark and Southern, Central, and Northern Sweden.

Details

Bayesian Econometrics
Type: Book
ISBN: 978-1-84855-308-8

1 – 10 of 56