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Dynamic Econometric Input-Output Modeling: New Perspectives

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Regional Research Frontiers - Vol. 2

Part of the book series: Advances in Spatial Science ((ADVSPATIAL))

Abstract

In this chapter we discuss some, in our view, fruitful future directions for econometric input-output (IO) modeling. In particular, we bring to the attention of practitioners of this line of research the important recent developments, both theoretical and empirical, in other fields of economics, in particular, in macroeconomics, agricultural economics, and post-Keynesian economics, which have been completely ignored in this strain of modeling. We highlight issues related to modeling of private consumption (consumers’ heterogeneity, socio-economic characteristics of households), and of production and trade (imperfect competition, technical change), data calibration, and real and financial stock-flow consistency. Given their importance and usefulness for a sound economic analysis, we think that regional research in general would benefit if these issues were incorporated into and/or appropriately adopted to the needs of econometric IO (or other relevant regional research) modeling.

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Notes

  1. 1.

    These countries include Austria, Belgium, Cyprus, Czech Republic, Denmark, Finland, France, Germany, Italy, Lithuania, Poland, Portugal, Romania, and Slovakia.

  2. 2.

    The derivation of the budget share w i with respect to log (C) and log (p j ) is given by β i and γ ij −β i (log(P)), respectively. Applying Shephard’s Lemma and using the Stone price approximation, the elasticity formulae can then be derived.

References

  • Almon C (1991) The INFORUM approach to interindustry modeling. Econ Syst Res 3(1):1–7

    Article  Google Scholar 

  • Almon C, Buckler M, Horwitz L, Reimbold T (1974) 1985: interindustry forecasts of the American economy. D.C. Heath, Lexington, MA

    Google Scholar 

  • Armington PS (1969) A theory of demand for products distinguished by place of production. IMF Staff Pap 16:159–178

    Article  Google Scholar 

  • Barker T (ed) (1976) Economic structure and policy. Chapman and Hall, London

    Google Scholar 

  • Barker T, Peterson W (1987) The cambridge multisectoral dynamic model of the British economy. Cambridge University Press, Cambridge

    Google Scholar 

  • Berg M, Hartley B, Richters O (2015) A stock-flow consistent input-output model with application to energy price shocks, interest rates, and heat emissions. New J Phys 17. doi:10.1088/1367-2630/17/1/015011

    Google Scholar 

  • Cambridge, DAE (Dept. of Economic Analysis) (1962) A programme for growth. A computable model for economic growth, vol 1

    Google Scholar 

  • Carroll CD (1997) Buffer-stock saving and the life cycle/permanent income hypothesis. Q J Econ 112:1–55

    Article  Google Scholar 

  • Carroll CD, Kimball MS (1996) On the concavity of the consumption function. Econometrica 64(4):981–992

    Article  Google Scholar 

  • Conway RS (1990) The Washington projection and simulation model: a regional interindustry econometric model. Int Reg Sci Rev 13:141–165

    Article  Google Scholar 

  • Deaton A, Muellbauer J (1980) An almost ideal demand system. Am Econ Rev 70(3):312–326

    Google Scholar 

  • Eggertson G, Krugman P (2012) Debt, deleveraging, and the liquidity trap: a Fisher-Minsky-Koo approach. Q J Econ 2012:1–45

    Google Scholar 

  • Gillingham K, Newell RG, Pizer WA (2008) Modeling endogenous technological change for climate policy analysis. Energy Econ 30:2734–2753

    Article  Google Scholar 

  • Godley W, Cripps F (1983) Macroeconomics. Fontana, London

    Google Scholar 

  • Godley W, Lavoie M (2007) Monetary economics: an integrated approach to credit, money, income, production and wealth. Palgrave Macmillan, New York

    Book  Google Scholar 

  • Green RD, Alston JM (1990) Elasticities in AIDS models. Am J Agric Econ 72:442–445

    Article  Google Scholar 

  • Hall RE (1978) Stochastic implications of the life cycle-permanent-income hypothesis: theory and evidence. J Polit Econ 86:971–987

    Article  Google Scholar 

  • Heckelei T, Britz W (2005) Models based on positive mathematical programming: state of the art and further extensions. In: Arfini F (ed) Modelling agricultural policies: state of the art and new challenges. Proceedings of the 89th European seminar of the European association of agricultural economics, University of Parma, Parma, Italy, pp 48–73

    Google Scholar 

  • Heckelei T, Britz W, Zhang Y (2012) Positive mathematical programming approaches—recent developments in literature and applied modelling. Bio-based Appl Econ 1:109–124

    Google Scholar 

  • Henry de Frahan B, Buysse J, Polomé P, Fernagut B, Harmignie O, Lauwers L, van Huylenbroeck G, van Meensel J (2007) Positive mathematical programming for agricultural and environmental policy analysis: review and practice. In: Weintraub A, Romero C, Bjorndal T, Epstein R, Miranda J (eds) Handbook of operations research in natural resources, International series of operations research & management science, vol 99. Springer, New York, pp 129–154

    Chapter  Google Scholar 

  • Howitt RE (1995) Positive mathematical programming. Am J Agric Econ 77:329–342

    Article  Google Scholar 

  • Jansson T, Heckelei T (2011) Estimating a primal model of regional crop supply in the European Union. J Agric Econ 62:137–152

    Article  Google Scholar 

  • Japelli T, Pistaferri L, Padula M (2008) A direct test of the buffer-stock model of saving. J Eur Econ Assoc 6(6):1186–1210

    Article  Google Scholar 

  • Jorgenson DW, Goettle R, Ho M, Wilcoxen P (2013) Energy, the environment and US economic growth. In: Dixon P, Jorgenson DW (eds) Handbook of CGE Modeling, vol 1. Elsevier, Amsterdam

    Google Scholar 

  • Kasnakoglu H, Bauer S (1988) Concept and application of an agricultural sector model for policy analysis in Turkey. In: Bauer S, Henrichsmeyer W (eds) Agricultural Sector Modelling. Proceedings of the 16th Symposium of the EAAE, Wissenschaftsverlag Vauk, Kiel, pp 71–84

    Google Scholar 

  • Kim K, Kratena K, Hewings GJD (2015) The extended econometric input-output model with heterogenous household demand system. Econ Syst Res 27(2):257–285

    Article  Google Scholar 

  • Kratena K, Sommer M (2014) Policy implications of resource constraints on the European economy. WWWforEurope Policy Brief, No 6, November 2014

    Google Scholar 

  • Kratena K, Streicher G, Temurshoev U, Amores AF, Arto I, Mongelli I, Rueda-Cantuche JM, Andreoni V (2013) FIDELIO 1: fully interregional dynamic econometric long-term input-output model for the EU 27. JRC Scientific and Policy Reports, JRC 81864, EU Commission, Joint Research Centre

    Google Scholar 

  • Langrell S (ed) (2013) Farm level modelling of CAP: a methodological overview. JRC Scientific and Policy Report, EUR 25873 EN, Publications Office of the European Union, Luxembourg

    Google Scholar 

  • Luengo-Prado MJ (2006) Durables, nondurables, down payments and consumption excesses. J Monet Econ 53:1509–1539

    Article  Google Scholar 

  • Luengo-Prado MJ, Sorensen BE (2004) The buffer-stock model and the aggregate propensity to consume: a panel-data study of the US states. CEPR Discussion Papers, No 4474, July 2004

    Google Scholar 

  • Lutz C, Meyer B, Wolter MI, (2005) GINFORS-Model, MOSUS Workshop. IIASA Laxenburg, 14–15 April 2005

    Google Scholar 

  • Meghir C, Pistaferri L (2010) Earnings, consumption and lifecycle choices. NBER Working Paper Series, 15914, April 2010

    Google Scholar 

  • Mérel P, Howitt R (2014) Theory and application of positive mathematical programming in agriculture and the environment. Ann Rev Resour Econ 6:451–447

    Article  Google Scholar 

  • Miyazawa K (1976) Input-output analysis and the structure of income distribution. Springer, Berlin

    Book  Google Scholar 

  • Mian A, Rao K, Sufi A (2013) Household balance sheets, consumption, and the economic slump. Q J Econ 2013:1687–1726

    Article  Google Scholar 

  • Naqvi AA (2015) Modeling growth, distributions and the environment in a stock-flow consistent framework. WWWforEurope Policy Paper 18

    Google Scholar 

  • Nyhus D (1991) The INFORUM international system. Econ Syst Res 3(1):55–64

    Article  Google Scholar 

  • Pan H (2006) Dynamic and endogenous change of input-output structure with specific layers of technology. Struct Chang Econ Dyn 17:200–223

    Article  Google Scholar 

  • Pan H, Köhler J (2007) Technological change in energy systems: learning curves, logistic curves and input-output coefficients. Ecol Econ 63:749–758

    Article  Google Scholar 

  • Paris Q, Drogué S, Anania G (2011) Calibrating spatial models of trade. Econ Model 28:2509–2516

    Article  Google Scholar 

  • Schumacher K, Sands RD (2007) Where are the industrial technologies in energy-economy models? An innovative CGE approach for steel production in Germany. Energy Econ 29:799–825

    Article  Google Scholar 

  • Sue Wing I (2006) Representing induced technological change in models for climate policy analysis. Energy Econ 28:539–762

    Article  Google Scholar 

  • Taylor L (2004) Reconstructing macroeconomics: structuralist proposals and critiques of the mainstream. Harvard University Press, Cambridge, MA

    Google Scholar 

  • Temurshoev U, Lantz F (2016) Long-term petroleum product supply analysis through a robust modelling approach. Loyola Econ Working Paper, Loyola University, Andalusia

    Google Scholar 

  • Temurshoev U, Mraz M, Delgado SL, Eder P (2015) EU petroleum refining fitness check: OURSE modelling and results. JRC Science for Policy Report, EUR 27269 EN, doi:10.2791/037768, Publications Office of the European Union, Luxembourg

    Google Scholar 

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Authors and Affiliations

  1. Centre of Economic Scenario Analysis and Research, Department of Economics, Loyola University Andalucía, Seville, Spain

    Kurt Kratena & Umed Temursho

Authors
  1. Kurt Kratena
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  2. Umed Temursho
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Correspondence to Kurt Kratena .

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Editors and Affiliations

  1. Regional Research Institute, West Virginia University, Morgantown, West Virginia, USA

    Randall Jackson

  2. Division of Resource Economics and Management, Faculty Research Associate, Regional Research Institute, West Virginia University, Morgantown, West Virginia, USA

    Peter Schaeffer

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Kratena, K., Temursho, U. (2017). Dynamic Econometric Input-Output Modeling: New Perspectives. In: Jackson, R., Schaeffer, P. (eds) Regional Research Frontiers - Vol. 2. Advances in Spatial Science. Springer, Cham. https://doi.org/10.1007/978-3-319-50590-9_1

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