Real effects of technology shocks: The case of Puerto Rico

  • Emanuelle A. Alemar University of Puerto Rico
  • Carlos A. Rodríguez University of Puerto Rico
DOI: https://doi.org/10.24201/ee.v36i2.419
Keywords: DSGE models, macroeconomics fluctuations, technological shocks, natural disasters, macroeconometrics, Bayesian estimation
JEL Classification: C02, C11, C61, C63, E32, E37

Abstract

This paper studies the effects of technology shocks reflected in anticipated and unanticipated changes in total factor productivity over macroeconomic fluctuations in Puerto Rico. For these purposes, Bayesian techniques are used to estimate the parameters of the technology process of a dynamic and stochastic general equilibrium model of the Hansen Real Economic CycleModel family (1985) with macroeconomic data from the Island. It is found that technology shocks on the Island have amplifying effects on production and hours worked, as small or moderate magnitude impulses results in fluctuations of greater magnitude in these variables, although the effects are not very persistent. On the other hand, it is estimated that the effects of Hurricane Maria resulted in a 4.2 percentage point reduction in total factor productivity in the fourth quarter of 2017, which is associated with contractions of up to 9 percentage points in production and 7 percentage points in working hours in the same period.

References

Adolfson, M., S. Laséen, J. Lindé y M. Villani. 2008. Evaluating an estimated new Keynesian small open economy model, Journal of Economic Dynamics and Control, 32(8): 2690-2721.

Alameda, J. 2007. Un estimado de las cuentas nacionales por trimestre para Puerto Rico, Ensayos y Monografías No. 134, Departamento de Economía, Universidad de Puerto Rico.

Alameda, J. y A. González. 2001. Cambio tecnológico, productividad y crecimiento económico en Puerto Rico, Ensayos y Monografías No. 106, Departamento de Economía, Universidad de Puerto Rico.

Altug, S. 1989. Time-to-build and aggregate fluctuations: Some new evidence, International Economic Review, 30(4): 889-920.

Arrow, K. 1965. Aspects of the Theory of Risk Bearing, Helsinki, Yrjo Jahnssonin Saatio.

Barsky, R. y E. Sims, 2011. News shocks and business cycles, Journal of Monetary Economics, 58(3): 273-289.

Blanchard, O. y C. Kahn. 1980. The solution of linear difference models under rational expectations, Econometrica, 48(5): 1305-1311.

Borda, P. y A. Wright. 2016. Macroeconomic fluctuations under natural disaster shocks in Central America and the Caribbean, IDB Working Paper Series No. 763.

Catalá, F. 1998. La economía de Puerto Rico, 1898-1998, Unidad de Investigaciones Económicas, Departamento de Economía, Universidad de Puerto Rico.

Christiano, L. y M. Eichenbaum. 1992. Current real-buisness cycle theories and aggregate labor market fluctuations, American Economic Review, 82(3): 430-445.

DeJong, D., B. Ingram y C. Whiteman. 2000. A Bayesian approach to dynamic macroeconomics, Journal of Econometrics, 98(2): 203-223.

Del Negro, M. y F. Schorfheide. 2009. Monetary policy analysis with potentially misspecified models, American Economic Review, 99(4): 1415-1450.

Dietz, J.L. 1989. Historia Económica de Puerto Rico, Puerto Rico, Ediciones Huracán.

Elekdag, S., A. Justiniano y I. Tchakarov. 2006. An estimated small open economy model of the financial accelerator, IMF Staff Papers, (53)2: 219-241.

Estado Libre Asociado de Puerto Rico. 1947. Constitución del Estado Libre Asociado, Gobierno de Puerto Rico.

Feliciano, Z. y A. Green. 2017. US multinationals in Puerto Rico and the repel of section 936 tax exemption for US corporations, NBER Working Paper No. 23681.

Fischer, S. 1977. Long-term contracts, rational expectations, and the optimal money supply rule, Journal of Political Economy, 85(1): 191-205.

Gelman, A. 2006. Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper), Bayesian Analysis, 1(3): 515-534.

Gomme, P. y D. Lkhagvasuren. 2013. Calibration and simulation of DSGE models, en N. Hashimzade y M. Thornton (eds.), Handbook of Research Methods and Applications in Empirical Macroeconomics, Nueva York, Edward Elgar Publishing.

Guerrón Quintana, P. y J. Nason. 2012. Bayesian estimation of DSGE models, Working Paper No. 12-4, Federal Reserve Bank of Philadelphia.

Haider, A. y S. Khan. 2008. A small open economy DSGE model for Pakistan, MPRA Paper No. 12977.

Hall, R. y C. Jones. 1998. Why do some countries produce so much more output per worker than others?, The Quarterly Journal of Economics, 114(1): 83- 116.

Hansen, G. 1985. Indivisible labor and the business cycle, Journal of Monetary Economics, 16(3): 309-327.

Hansen, L. y K. Singleton. 1983. Stochastic consumption, risk aversion, and the temporal behavior of asset returns, Journal of Political Economy, 91(2): 249-265.

Herbst, E. y F. Schorfheide. 2015. Bayesian Estimation of DSGE Models, Princeton University Press, Princeton: Nueva Jersey.

Hodrick, R.J. y E. Prescott. 1981. Postwar U.S. business cycles: An empirical investigation, Discussion Paper No. 451, Center for Mathematical Studies in Economics and Management Science, Northwestern University.

Ireland, P. 2001. Sticky-price models of the business cycle: Specification and stability, Journal of Monetary Economics, 47(1): 3-18.

Iskrev, N. 2008. Evaluating the information matrix in linearized DSGE models, Economics Letters, 99(3): 607-610.

Junta de Planificación. 2018. Apéndice estadístico del informe económico al gobernador, Gobierno de Puerto Rico.

Kim, J. 2000. Constructing and estimating a realistic optimizing model of monetary policy, Journal of Monetary Economics, 45(2): 329-359.

Kydland, F. y E. Prescott. 1982. Time to build and aggregate fluctuations, Econometrica, 50(2): 1345-1370.

Lubik, T. y F. Schorfheide. 2005. A Bayesian look at new open economy macroeconomics, NBER Macroeconomics Annual, 20: 313-366.

Lucas, R. 1976. Econometric policy evaluation: A critique, Carnegie-Rochester Conference Series on Public Policy, 1: 19-46.

Martínez, J., J. Máttar y P. Rivera. 2005. Globalización y Desarrollo: Desafíos de Puerto Rico frente al Siglo XXI, México, CEPAL.

McCallum, B. 1998. Solutions to linear rational expectations models: A compact exposition, Economics Letters, 61(2): 143-147.

McCandless, G. 2008. The ABC’s of RBC’s, Harvard University Press, Cambridge: Massachusetts.

McGrattan, E. 1994. The macroeconomic effects of distortionary taxation, Journal of Monetary Economics, 33(3): 573-601.

McKnight, S., A. Mihailov y A. Pompa-Rangel. 2020. What do Latin American inflation targeters care about? A comparative Bayesian estimation of central bank preferences, Journal of Macroeconomics, 63: 103188.

Onatski, A. y N. Williams. 2004. Empirical and policy performance of a forward-looking monetary model, Unpublished Manuscript, Department of Economics, Princeton University.

Otrok, C. 2001. On measuring the welfare cost of business cycles, Journal of Monetary Economics, 47(1): 61-92.

Pfeifer, J. 2014. A guide to specifying observation equations for the estimation of DSGE models, Research Series, Universitat der Bundeswehr Munchen.

Phelps, E.S. 1966. Golden Rules of Economic Growth: Studies of Efficient and Optimal Investment, Nueva York, Norton, W. W. & Company, Inc.

Roberts, G., A. Gelman y W. Gilks. 1997. Weak convergence and optimal scaling of random walk metropolis algorithms, The Annals of Applied Probability, 7(1): 110-120.

Rodríguez, C.A. 2017. Un análisis dinámico de los impulsos de oferta y demanda en Puerto Rico y la política monetaria de Estados Unidos utilizando la descomposición estructural Blanchard-Quah, Análisis Económico, 32(81): 5-30.

Rodríguez, C.A. y W. Toledo. 2007. Efectos de la tasa de los fondos federales de los Estados Unidos en una economía pequeña, abierta y dolarizada: el caso de Puerto Rico, El Trimestre Económico, 74(293): 223-246.

Sargent, T. 1989. Two models of measurements and the investment accelerator, Journal of Political Economy, 97(2): 251-287.

Schorfheide, F. 2000. Loss function-based evaluation of DSGE models, Journal of Applied Econometrics, 15(6): 645-670.

Sims, E. 2011. Graduate macro theory II: Extensions of the basic RBC framework, University of Notre Dame.

Smets, F. y R. Wouters. 2007. Shocks and frictions in US business cycles: A Bayesian DSGE approach, American Economic Review, 97(3): 586-606.

Toledo, W. 2006. Avances tecnológicos y las fluctuaciones económicas, evidencia del sector de la manufactura de Puerto Rico, EconoQuantum, 3(1): 35-61.

West, M. y J. Harrison. 1997. Bayesian Forecasting and Dynamic Models, Springer, Nueva York: Nueva York.

Published
08-10-2021
How to Cite
AlemarE., & RodríguezC. (2021). Real effects of technology shocks: The case of Puerto Rico. Estudios Económicos, 36(2), 235-277. https://doi.org/10.24201/ee.v36i2.419
Issue
72-vol. 36, no. 2, july-december, 2021
Section
Articles
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