超越总量：长期增长建模的特定行业框架（英）

11127 Produced by the Research Support TeamAbstractThe Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about developmentissues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry thenames of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely thoseof the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank andits affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.Policy Research Working Paper11127This paper develops a bottom-up, sector-specific approachto modeling potential output that overcomes limitations oftraditional top-down estimates for long-term projectionsand policy analysis. The model disaggregates total-factorproductivity (TFP) growth into within-sector productivityeffects and between-sector reallocations. Such endogenousbetween effects capture structural transformation, notablythe shift from low-productivity sectors like agriculture tohigher-productivity industrial and service sectors—a keydriver of growth in developing countries. At the heart ofThis paper is a product of the Economic Policy Global Department. It is part of a larger effort by the World Bank toprovide open access to its research and make a contribution to development policy discussions around the world. PolicyResearch Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contactedat cjooste@worldbank.org and rtercioglu@worldbank.org. the framework, wedges in sectoral factor prices, substi-tution elasticities, and productivity differentials describethe contribution of between-effects to aggregate produc-tivity. Although the approach here can be applied to anymacro-structural model, its benefits are illustrated by intro-ducing it into the World Bank’s semi-structural models forGhana and the Kyrgyz Republic to showcase its potential toenhance the analysis of long-run growth dynamics throughstructural change. BeyondAggregates:ASector-SpecificFrameworkforLong-TermGrowthModeling∗CharlJooste1,RemziBarisTercioglu11EconomicPolicyGlobalPractice,WorldBank,Washington,DCJEL Classification:C10, C50, Q43Keywords:Economic modeling, structural change∗We thank Andrew Burns, Florent McIsaac, Andreas Eberhard, Frederico Gil Sander, James Sampi,Ekaterina Vostroknutova, Lazar Milivojevic, Stefano Curto, Chung Gu Chee and Ragchaasuren Galindevfor helpful comments. The authors thank the multi-donor Climate Support Facility for funding this work.The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. Theydo not necessarily represent the views of the International Bank for Reconstruction and Development/-World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or thegovernments they represent. 1IntroductionSemi-structural macroeconomic models are extensively used by central banks (Angelini et al.,2019; Lemoine et al., 2018; Brayton et al., 1997; Cusbert, Kendall, et al., 2018), ministries offinance (Bullen et al., 2021; Welfe, 2011; Dam, 1987; Dudek et al., 2012), international insti-tutions (Burns et al., 2019) and the private sector for macroeconomic projections and policysimulations. While some versions of these models include detailed sectoral representations,these models tend to focus on aggregate quantities and often feature stylized representationsof general equilibrium.They typically focus on short- to medium-term developments andare content to leave much of the determinants of growth to an aggregate potential outputfunction. The models tend to have limited sectoral detail and limited endogenous long-rundynamics.For more granular growth and sectoral studies, planning ministries and central banksfrequently rely on a range of modeling tools.For instance, they may rely on DynamicRecursive Computable General Equilibrium (DRCGE) (Robinson and Roland-Holst, 1988;Callonnec et al., 2013; Robinson, 1991; Davis, 2004; Roson and Mensbrugghe, 2018), andgrowth models are preferred for analyzing long-term trends (Rebelo, 1991; Srinivasan, 1995;Hevia and Loayza, 2012; Devadas and Pennings, 2018). Some exciting new work over the pastfew years has built out network structures to account for sectoral spill-overs - the frameworkof Baqaee and Farhi (2020) achieves this objective and can be used to map onto dynamicstructural macroeconomic models.Other macroeconomic models provide a more detailed representation of the economy byincorporating richer sectoral details and productivity variations. For instance, Boppart et al.(2023) demonstrate that capital and intermediate input costs decline more rapidly than laborcosts across most sectors, with the exception of agriculture.Thi