Results 1  10
of
47
Estimating multicountry VAR models
 International Economic Review
, 2009
"... This paper presents a method to estimate the coefficients, to test specification hypotheses and to conduct policy exercises in multicountry VAR models with cross unit interdependencies, unit specific dynamics and time variations in the coefficients. The framework of analysis is Bayesian: a prior fl ..."
Abstract

Cited by 42 (8 self)
 Add to MetaCart
This paper presents a method to estimate the coefficients, to test specification hypotheses and to conduct policy exercises in multicountry VAR models with cross unit interdependencies, unit specific dynamics and time variations in the coefficients. The framework of analysis is Bayesian: a prior flexibly reduces the dimensionality of the model and puts structure on the time variations; MCMC methods are used to obtain posterior distributions; and marginal likelihoods to check the fit of various specifications. Impulse responses and conditional forecasts are obtained with the output of a MCMC routine. The transmission of certain shocks across countries is analyzed.
Firm growth and R&D Expenditure
 Economics of Innovation and New Technology
, 2010
"... We apply a panel vector autoregression model to a firmlevel longitudinal database to observe the coevolution of sales growth, employment growth, profits growth and growth of R&D expenditure. Contrary to expectations, profit growth seems to have very little detectable effect on R&D investme ..."
Abstract

Cited by 20 (3 self)
 Add to MetaCart
We apply a panel vector autoregression model to a firmlevel longitudinal database to observe the coevolution of sales growth, employment growth, profits growth and growth of R&D expenditure. Contrary to expectations, profit growth seems to have very little detectable effect on R&D investment. Instead, firms appear to increase their total R&D expenditure following growth in sales and growth of employment. In a sense, firms behave ‘as if ’ they aim for a roughly constant ratio of R&D to employment (or sales). We observe heterogeneous effects for growing or shrinking firms however, suggesting that firms are less willing to reduce their R&D levels following a negative growth shock than they are willing to increase R&D after a positive shock.
A Parallel CuttingPlane Algorithm for the Vehicle Routing Problem With Time Windows
, 1999
"... In the vehicle routing problem with time windows a number of identical vehicles must be routed to and from a depot to cover a given set of customers, each of whom has a specified time interval indicating when they are available for service. Each customer also has a known demand, and a vehicle may on ..."
Abstract

Cited by 19 (1 self)
 Add to MetaCart
In the vehicle routing problem with time windows a number of identical vehicles must be routed to and from a depot to cover a given set of customers, each of whom has a specified time interval indicating when they are available for service. Each customer also has a known demand, and a vehicle may only serve the customers on a route if the total demand does not exceed the capacity of the vehicle. The most effective solution method proposed to date for this problem is due to Kohl, Desrosiers, Madsen, Solomon, and Soumis. Their algorithm uses a cuttingplane approach followed by a branchand bound search with column generation, where the columns of the LP relaxation represent routes of individual vehicles. We describe a new implementation of their method, using Karger's randomized minimumcut algorithm to generate cutting planes. The standard benchmark in this area is a set of 87 problem instances generated in 1984 by M. Solomon; making using of parallel processing in both the cuttingpla...
CURRENT ACCOUNT BENCHMARKS FOR CENTRAL AND EASTERN EUROPE A DESPERATE SEARCH? 1
, 2009
"... Current account benchmarks for central and eastern Europe a desperate search? by Michele Ca ’ Zorzi, ..."
Abstract

Cited by 12 (3 self)
 Add to MetaCart
Current account benchmarks for central and eastern Europe a desperate search? by Michele Ca ’ Zorzi,
QML estimation of dynamic panel data models with spatial errors. Working Paper
, 2007
"... We propose quasi maximum likelihood (QML) estimation of dynamic panel models with spatial errors when the crosssectional dimension n is large and the time dimension T is fixed. We consider both the random effects and fixed effects models and derive the limiting distributions of the QML estimators u ..."
Abstract

Cited by 8 (0 self)
 Add to MetaCart
(Show Context)
We propose quasi maximum likelihood (QML) estimation of dynamic panel models with spatial errors when the crosssectional dimension n is large and the time dimension T is fixed. We consider both the random effects and fixed effects models and derive the limiting distributions of the QML estimators under different assumptions on the initial observations. We propose a residualbased bootstrap method for estimating the standard errors of the QML estimators. Monte Carlo simulation shows that both the QML estimators and the bootstrap standard errors perform well in finite samples under a correct assumption on initial observations, but may perform poorly when this assumption is not met.
FORECASTING WITH PANEL DATA
"... This Working Paper is brought to you for free and open access by the Maxwell School of Citizenship and Public Affairs at SURFACE. It has been accepted for inclusion in Center for Policy Research by an authorized administrator of SURFACE. For more information, please contact ..."
Abstract

Cited by 8 (1 self)
 Add to MetaCart
This Working Paper is brought to you for free and open access by the Maxwell School of Citizenship and Public Affairs at SURFACE. It has been accepted for inclusion in Center for Policy Research by an authorized administrator of SURFACE. For more information, please contact
Estimation of dynamic panel data models with sample selection, fothcoming in
 J. Appl. Econ.
, 2012
"... Summary We propose a new method for estimating dynamic panel data models with selection. The method uses backward substitution for the lagged dependent variable, which leads to an estimating equation that requires correcting for contemporaneous selection only. The estimator is valid under relativel ..."
Abstract

Cited by 7 (0 self)
 Add to MetaCart
Summary We propose a new method for estimating dynamic panel data models with selection. The method uses backward substitution for the lagged dependent variable, which leads to an estimating equation that requires correcting for contemporaneous selection only. The estimator is valid under relatively weak assumptions about errors and permits avoiding the weak instruments problem associated with differencing. We also propose a simple test for selection bias that is based on the addition of a selection term to the firstdifference equation and subsequent testing for significance of this term. The methods are applied to estimating dynamic earnings equations for women.
2003), "Panel Index VAR Models: Specification, Estimation, Testing and Leading Indicators ", CEPR Discussion Paper no
"... IVIE working papers offer in advance the results of economic research under way in order to encourage a discussion process before sending them to scientific journals for their final publication. ..."
Abstract

Cited by 3 (0 self)
 Add to MetaCart
(Show Context)
IVIE working papers offer in advance the results of economic research under way in order to encourage a discussion process before sending them to scientific journals for their final publication.
Combining time series and cross sectional data for the analysis of dynamic marketing systems. Working Paper
, 2002
"... SOMtheme F Interactions between consumers and rms Vector AutoRegressive (VAR) models have become popular in analyzing the behavior of competitive marketing systems. However, an important drawback of VAR models is that the number of parameters to be estimated can become very large. This may cause es ..."
Abstract

Cited by 3 (0 self)
 Add to MetaCart
SOMtheme F Interactions between consumers and rms Vector AutoRegressive (VAR) models have become popular in analyzing the behavior of competitive marketing systems. However, an important drawback of VAR models is that the number of parameters to be estimated can become very large. This may cause estimation problems, due to a lack of degrees of freedom. In this paper, we consider a solution to these problems. Instead of using a single time series, we develop pooled models that combine time series data for multiple units (e.g. stores). These approaches increase the number of available observations to a great extent and thereby the efciency of the parameter estimates. We present a small simulation study that demonstrates this gain in efciency. An important issue in estimating pooled dynamic models is the heterogeneity among cross sections, since the mean parameter estimates that are obtained by pooling heterogenous cross sections may be biased. In order to avoid these biases, the model should accommodate a sufcient degree of heterogeneity. At the same time, a model that needlessly allows for heterogeneity requires the estimation of extra parameters and hence, reduces efciency of the parameter estimates. So, a thorough investigation of heterogeneity should precede the choice of the nal model. We discuss pooling approaches that accommodate for parameter heterogeneity in different ways and we introduce several tests for investigating crosssectional heterogeneity that may facilitate this choice. We provide an empirical application using data of the Chicago market of the three largest national
Search, liquidity, and the dynamics of house prices and construction
 American Economic Review
, 2014
"... The dynamics of house prices, sales, construction and population growth in are characterized response to cityspeci
c income shocks for 106 U.S. cities. A dynamic search model of the housing market is then developed in which construction, the entry of buyers, house prices and sales are determined in ..."
Abstract

Cited by 3 (0 self)
 Add to MetaCart
The dynamics of house prices, sales, construction and population growth in are characterized response to cityspeci
c income shocks for 106 U.S. cities. A dynamic search model of the housing market is then developed in which construction, the entry of buyers, house prices and sales are determined in equilibrium. The theory generates dynamics qualitatively consistent with the observations and a version calibrated to match key features of the U.S. housing market o¤ers a substantial quantitative improvement over models without search. In particular, variation in the time it takes to sell (i.e. the houses liquidity) induces transaction prices to exhibit serially correlated growth.