A STRUCTURAL BRIDGE BETWEEN INPUT-OUTPUT ANALYSIS AND SEMI-STRUCTURAL MACROECONOMETRIC MODELLING: EVIDENCE FROM MOLDOVA
DOI:
https://doi.org/10.36004/nier.es.2026.1-03Keywords:
input-output analysis, macroeconometric model, bridge methodology, small open economy, Leontief multipliers, counterfactual scenariosAbstract
This paper develops a parsimonious structural bridge linking semi-structural macroeconometric estimation with input-output sectoral analysis for the Republic of Moldova, addressing the analytical gap between aggregate forecasting and sectoral diagnostics in small post-Soviet economies. The methodology proceeds in three steps: macroeconomic shocks are translated into expenditure-side aggregates using OLS elasticities; aggregate changes are distributed across 20 NACE Rev.2 sectors using two alternative weighting schemes (one IO-derived, the other derived independently from BNS customs export data); sectoral output impacts are obtained via Leontief multiplication. Aggregate impacts converge within ±2% across schemes despite substantial sectoral divergence, providing evidence that economy-wide results are robust to the choice of export weighting. Four counterfactual scenarios are examined: a 5% EU27 demand contraction generates a 9.8% reduction in total gross output, with 26% accruing to non-export sectors via supply-chain channels invisible in aggregate models; a 10% fiscal revenue increase yields a sub-unitary multiplier (1.03) reflecting import leakage; a 15% currency depreciation generates zero sectoral impact under strict elasticities; single-sector shocks reveal a duality of static IO under demand and supply interpretations. The methodology is reproducible from public data and transferable to comparable post-Soviet economies.
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Bańbura, M., Giannone, D., & Reichlin, L. (2010). Large Bayesian Vector Auto Regressions. Journal of Applied Econometrics, 25(1), 71-92. https://doi.org/10.1002/jae.1137
Baqaee, D. R., & Farhi, E. (2019). The macroeconomic impact of microeconomic shocks: Beyond Hulten's theorem. Econometrica, 87(4), 1155-1203. https://doi.org/10.3982/ECTA15202
Barker, T. (1999). Achieving a 10% Cut in Europe's Carbon Dioxide Emissions Using Additional Excise Duties: Coordinated, Uncoordinated and Unilateral Action Using the Econometric Model E3ME. Economic Systems Research, 11(4), 401-421. https://doi.org/10.1080/09535319900000029
Bradley, J., & Untiedt, G. (2008). Analysis of EU Cohesion Policy 2000-2006 Using the CSHM HERMIN Model: Notes on Working Methods. GEFRA Working Paper 7. Münster: GEFRA.
Bussière, M., Callegari, G., Ghironi, F., Sestieri, G., & Yamano, N. (2013). Estimating Trade Elasticities: Demand Composition and the Trade Collapse of 2008-2009. American Economic Journal: Macroeconomics, 5(3), pp. 118-151. https://www.aeaweb.org/articles?id=10.1257/mac.5.3.118
Cogley, T., & Sargent, T. J. (2005). Drifts and volatilities: monetary policies and outcomes in the post WWII US. Review of Economic Dynamics, 8(2), 262-302. https://doi.org/10.1016/j.red.2004.10.009
Dietzenbacher, E., & Los, B. (1998). Structural Decomposition Techniques: Sense and Sensitivity. Economic Systems Research, 10(4), 307-323. https://doi.org/10.1080/09535319800000023
Garcia, A. (2024). Multi-Sector Inflation in Small Open Economies: Theory and Evidence from Chile and the United Kingdom. Working Paper. Banco Central de Chile.
Goldstein, M., & Khan, M. S. (1985). Income and Price Effects in Foreign Trade. Chapter 20. In: R. W. Jones & P. B. Kenen (Eds.), Handbook of International Economics (Vol. 2, pp. 1041-1105). Amsterdam: Elsevier. https://www.sciencedirect.com/science/chapter/handbook/abs/pii/S1573440485020111?via%3Dihub
Hommes, C., & Poledna, S. (2026). Agent-Based Forecasting at Central Banks: Methodology and Applications. Working Paper. Bank of Canada.
Hooper, P., Johnson, K., & Marquez, J. (2000). Trade Elasticities for the G-7 Countries. Princeton Studies in International Economics 87. Princeton University. https://ies.princeton.edu/pdf/S87.pdf
International Monetary Fund (IMF). (2024). Republic of Moldova: 2024. Article IV Consultation. International Monetary Fund. https://www.imf.org/-/media/files/publications/cr/2024/english/1mdaea2024001-print-pdf.pdf
Junius, T., & Oosterhaven, J. (2003). The Solution of Updating or Regionalizing a Matrix with Both Positive and Negative Entries. Economic Systems Research, 15(1), 87-96. https://doi.org/10.1080/0953531032000056954
Kratena, K., & Wüger, M. (2010). The full impact of energy efficiency on households' energy demand. WIFO Working Paper 356. Vienna: WIFO. https://www.wifo.ac.at/publication/113581/
Lutz, C., Meyer, B., & Wolter, M. I. (2010). The Global Multisector/Multicountry 3-E Model GINFORS. A description of the model and a baseline forecast for global energy demand and CO 2 emissions. International Journal of Global Environmental Issues, 10(1/2), 25-45. https://ideas.repec.org/a/ids/ijgenv/v10y2010i1-2p25-45.html
Mercure, J.-F., Pollitt, H., Edwards, N. R., Holden, P. B., Chewpreecha, U., Salas, P., Lam, A., Knobloch, F., & Vinuales, J. E. (2018). Environmental impact assessment for climate change policy with the simulation-based integrated assessment model E3ME-FTT-GENIE. Energy Strategy Reviews, 20, 195-208. https://doi.org/10.1016/j.esr.2018.03.003
Meyer, B., & Lutz, C. (2007). The GINFORS model: Concept and application. Paper presented at the OECD Workshop on Global Convergence Scenarios: Structural and Policy Issues. Paris: OECD.
Mija, S. (2022). Using of Statistical and Econometric Methods in Fundamentation of Monetary Policy Oriented to Price Stability. PhD Dissertation. Chișinău: Academy of Economic Studies of Moldova. http://www.cnaa.md/en/thesis/58113/
Mija, S., Slobozian, D., Cuhal, R., & Stratan, A. (2013). How Core Inflation Reacts to the Second Round Effects. Romanian Journal of Economic Forecasting, 16(1), 98-118. https://rses.ince.md/handle/123456789/269
Miller, R. E., & Blair, P. D. (2022). Input-Output Analysis. Foundations and Extensions (3rd ed.). Cambridge: Cambridge University Press. https://assets.cambridge.org/97811084/84763/frontmatter/9781108484763_frontmatter.pdf
Naval, E. (2019). Experience of the Input-Output Models Application to the Moldovan Economy. Economy and Sociology, 1, 36-52. https://doi.org/10.36004/nier.es.2019.1-03
Pârțachi, I., & Mija, S. (2013). Monetary Policy Transmission Mechanism Using Econometric Models. Romanian Statistical Review. Romanian Statistical Review Supplement, 61(4), 148-157. https://ideas.repec.org/a/rsr/supplm/v61y2013i4p148-157.html
Pârțachi, I., & Mija, S. (2015a). A Semi-Structural General Equilibrium Analysis of Moldova's Monetary Policy Transmission Mechanism. Economic Research Guardian, 5(1), 34-47. https://ideas.repec.org/a/wei/journl/v5y2015i1p34-47.html
Pârțachi, I., & Mija, S. (2015b). Monetary Policy - Instrument for Macroeconomic Stabilization. Procedia Economics and Finance, 20, 485-493. https://doi.org/10.1016/S2212-5671(15)00100-8
Pârțachi, I., & Mija, S. (2024). Moldova GDP Forecasting Using Bayesian Multivariate Models. Revista Economica, 76(1), 85-93. https://doi.org/10.56043/reveco-2024-0008
Poledna, S., Miess, M. G., Hommes, C., & Rabitsch, K. (2023). Economic forecasting with an agent-based model. European Economic Review, 151, January, 104306. https://doi.org/10.1016/j.euroecorev.2022.104306
Pyatt, G., & Round, J. I. (Eds.). (1985). Social Accounting Matrices: A Basis for Planning. Washington, DC: World Bank. https://documents1.worldbank.org/curated/en/919371468765880931/pdf/multi-page.pdf
Rose, A., & Liao, S.-Y. (2005). Modeling Regional Economic Resilience to Disasters: A Computable General Equilibrium Analysis of Water Service Disruptions. Journal of Regional Science, 45(1), 75-112. https://doi.org/10.1111/j.0022-4146.2005.00365.x
Sommer, M., & Kratena, K. (2017). The Carbon Footprint of European Households and Income Distribution. Ecological Economics, 136, 62-72. https://doi.org/10.1016/j.ecolecon.2016.12.008
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