Is Globalization Driving Efficiency? A Threshold Stochastic Frontier Panel Data Modelling Approach

SERIES Working Paper No. 40

27 Pages Posted: 28 Jul 2012

See all articles by Camilla Mastromarco

Camilla Mastromarco

Dipartimento di Scienze dell'Economia - University of Salento (Lecce)

Laura Serlenga

Università degli Studi di Bari; Institute for the Study of Labor (IZA)

Yongcheol Shin

Independent

Date Written: October 21, 2011

Abstract

Recently, Mastromarco, Serlenga and Shin (2010) propose a two-step approach to examine dynamic transmission mechanism under which globalization factors foster technology efficiency. In this paper, we extend the MSS model by combining panel threshold regression technique advanced by Hansen (1999). This threshold stochastic frontier panel data model enables us to analyze regime-specific stochastic frontiers and complex time-varying patterns of technical efficiencies in a robust manner. Using a dataset of 44 countries over 1970-2007, we find that income elasticities of labour and capital and time-varying common efficiencies are substantially different under superior and inferior frontiers. Capital and labour inputs are more productive under superior frontier. More importantly, common efficiencies have steadily increased under superior frontier, but technical efficiency has monotonically decreased for low income countries, supporting the so-called club convergence hypothesis. Furthermore, the VAR-based impulse response analyses suggest that openness factors through FDI and trade help the countries improve production technology and efficiency position relative to the frontier only after the country has reached a certain level of development.

Keywords: Threshold Stochastic Frontier Models in Heterogeneous Panels, Globalization Factors and Unobserved Factors, Time-Varying Efficiencies, Impulse Response Analyses

JEL Classification: D24, O47, C13, C33

Suggested Citation

Mastromarco, Camilla and Serlenga, Laura and Shin, Yongcheol, Is Globalization Driving Efficiency? A Threshold Stochastic Frontier Panel Data Modelling Approach (October 21, 2011). SERIES Working Paper No. 40, Available at SSRN: https://ssrn.com/abstract=2118478 or http://dx.doi.org/10.2139/ssrn.2118478

Camilla Mastromarco (Contact Author)

Dipartimento di Scienze dell'Economia - University of Salento (Lecce) ( email )

Ecotekne
Strada per Monteroni
Lecce 73100
Italy

Laura Serlenga

Università degli Studi di Bari ( email )

Piazza Umberto I
Bari, 70121
Italy

Institute for the Study of Labor (IZA) ( email )

P.O. Box 7240
Bonn, D-53072
Germany

Yongcheol Shin

Independent

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
40
Abstract Views
547
PlumX Metrics