Sage Journals: Discover world-class research

Abstract

The interdependence among decision-making units challenges the assumption of cross-sectional independence in traditional stochastic frontier models. Based on the seminal spatial Durbin specification for the frontier function, Galli (2023, Journal of the Royal Statistical Society, C ser., 72: 346-367) introduced inefficiency spillovers to measure neighborhood effects related to the inefficiency determinants. This article presents a new command, sfsd, that fits the comprehensive spatial stochastic frontier model that Galli (2023) proposed, accommodating various spatial and nonspatial specifications in both the frontier and the inefficiency equations. sfsd is the first command that includes different typologies of spatial spillovers in a stochastic frontier framework, facilitating the investigation of contemporary research topics such as agglomeration and technology diffusion at both the firm and the regional levels. The description, options, and illustrative examples for the command are outlined in this article.

Keywords

st0771 sfsd spatial stochastic frontier models spillover effects technical efficiency inefficiency spillovers

Get full access to this article

View all access options for this article.

References

Adetutu

Glass

A. J.

Kenjegalieva

Sickles

R. C.

. 2015.The effects of efficiency and TFP growth on pollution in Europe: A multistage spatial analysis. Journal of Productivity Analysis 43: 307–326. 10.1007/s11123-0140426-7.

Aigner

D. J.

Lovell

C. A. K.

Schmidt

. 1977. Formulation and estimation of stochastic frontier production function models. Journal of Econometrics 6: 21–37 10.1016/0304-4076(77)90052-5.

Areal

F. J.

Pede

V. O.

. 2021. Modeling spatial interaction in stochastic frontier analysis. Frontiers in Sustainable Food Systems 58: art. 673–039. 103389/fsufs.2021.673039.

Battese

G. E.

Coelli

T. J.

. 1988. Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data. Journal of Econometrics 38: 387399. 10.1016/0304-4076(88)90053-X.

______. 1995. A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical Economics 20: 325–332. 10.1007/BF01205442.

Belotti

Daidone

Ilardi

Atella

. 2013. Stochastic frontier analysis using Stata. Stata Journal 13: 719–758. 10.1177/1536867X1301300404.

Caudill

S. B.

Ford

J. M.

Gropper

D. M.

. 1995. Frontier estimation and firm-specific inefficiency measures in the presence of heteroscedasticity. Journal of Business and Economic Statistics 13: 105–111. 10.1080/07350015.199510524583.

Copeland

B. R

. 1991. Tourism, welfare and de-industrialization in a small open economy. Economica 58: 515–519. 10.2307/2554696.

Delgado

Porter

M. E.

Stern

. 2014. Clusters, convergence, and economic performance. Research Policy 43: 1785–1799. 10.1016/j.respol.201405.007.

10.

Ditzen

, W. Grieser, and M. Zekhnini. 2023. nwxtregress: Network regressions in Stata. GitHub. https://janditzen.github.io/nwxtregress/ .

11.

Drukker

D. M.

Peng

Prucha

I. R.

Raciborski

. 2013. Creating and managing spatial-weighting matrices with the spmat command. Stata Journal 13: 242–286 10.1177/1536867X1301300202.

12.

Orea

Alvarez

I. C.

. 2024. Fitting spatial stochastic frontier models in Stata. Stata Journal 24: 402–426. 10.1177/1536867X241276109.

13.

Galli

. 2023. A spatial stochastic frontier model introducing inefficiency spillovers. Journal of the Royal Statistical Society, C ser., 72: 346–367. 101093/jrsssc/qlad012.

14.

____. 2024. Accounting for unobserved individual heterogeneity in spatial stochastic frontier models: The case of Italian innovative start-ups. Spatial Economic Analysis 19: 620–645. 10.1080/17421772.2024.2306953.

15.

Glass

A. J.

Kenjegalieva

Sickles

R. C.

. 2016. A spatial autoregressive stochastic frontier model for panel data with asymmetric efficiency spillovers. Journal of Econometrics 190: 289–300. 10.1016/jjeconom.2015.06.011.

16.

Gude

Alvarez

Orea

. 2018. Heterogeneous spillovers among Spanish provinces: A generalized spatial stochastic frontier model. Journal of Productivity. Analysis 50: 155–173. 10.1007/s11123-018-0540-z.

17.

Hadri

. 1999. Estimation of a doubly heteroscedastic stochastic frontier cost function. Journal of Business and Economic Statistics 17:359–363. 10.108007350015.1999.10524824.

18.

Jondrow

Lovell

C. A. K.

Materov

I. S.

Schmidt

. 1982. On the estimation of technical inefficiency in the stochastic frontier production function model. Journal of Econometrics 19: 233–238. 10.1016/0304-4076(82)90004-5.

19.

Karakaplan

M. U

. 2017. Fitting endogenous stochastic frontier models in Stata. Stata Journal 17: 39–55. 10.1177/1536867X1701700103.

20.

_____. 2022. Panel stochastic frontier models with endogeneity. Stata Journal 22: 643–663. 10.1177/1536867X221124539.

21.

Kumbhakar

S. C.

Lovell

C. A. K.

. 2000. Stochastic Frontier Analysis. Cambridge, Cambridge University Press. 10.1017/CBO9781139174411.

22.

Kutlu

Tran

K. C.

Tsionas

M. G.

. 2020. A spatial stochastic frontier model with endogenous frontier and environmental variables. European Journal of Operational Research 286: 389–399. 10.1016/j.ejor.2020.03.020.

23.

LeSage

Pace

R. K.

. 2009. Introduction to Spatial Econometrics . Boca Raton FL: Chapman and Hall/CRC. 10.1201/9781420064254.

24.

Lian

Liu

Parmeter

C. F.

. 2023. Two-tier stochastic frontier analysis using Stata. Stata Journal 23: 197–229. 10.1177/1536867X231162033.

25.

Marrocu

Paci

. 2011. They arrive with new information. Tourism flows and production efficiency in the European regions. Tourism Management 32: 750–758 10.1016/j.tourman.2010.06.010.

26.

Meeusen

van den Broeck

. 1977. Efficiency estimation from Cobb-Douglas production functions with composed error. International Economic Review 18: 435–444. 10.2307/2525757.

27.

Orea

Alvarez

I. C.

Jamasb

. 2018. A spatial stochastic frontier model with omitted variables: Electricity distribution in Norway. Energy Journal 39: 93–116. 10.5547/01956574.39.3.lore

28.

Porter

. 1998. Clusters and the new economics of competition. Harvard Business Review 76:77–90.

29.

Tsukamoto

. 2019. A spatial autoregressive stochastic frontier model for panel data incorporating a model of technical inefficiency. Japan and the World Economy 50: 66–77. 10.1016/j.japwor.2018.11.003.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.14 MB

0.00 MB

A command to fit spatial stochastic frontier models with inefficiency spillovers

Abstract

Keywords

Get full access to this article

References

Supplementary Material