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Economic Growth

Too Many Buildings, Too Few Machines: How the Composition of Credit Shapes Long-Run Growth

Posted by e-axes on April 21, 2026

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The sectoral composition of credit and long-run growth

In this paper Paul W. Dai, Karsten Müller, and Emil Verner are addressing the question of whether the composition of credit, and not just its overall level, shape the relationship between financial deepening and long-run economic growth, and if so, what forces drive the reallocation of credit across sectors over the course of economic development.

The authors assemble a new cross-country panel covering 79 countries from 1970 to 2020, using an updated version of the Global Credit Project database (Müller and Verner, 2024) that breaks outstanding firm credit into four broad sectors: agriculture, manufacturing (incl. mining), construction and real estate, and services. They combine this with sectoral value-added and employment data from EU KLEMS, Groningen GGDC, UN, UNIDO, OECD STAN, WIOD, and ECLAC. They also develop a two-sector general-equilibrium model combining a Kiyotaki–Moore (1997) collateral constraint with a Ngai–Pissarides (2007) supply-side structural-change setup, where real estate serves as both production input and collateral.

Findings

  • Financial deepening is highly unbalanced. As countries get richer, total firm credit/GDP rises, but this masks a large reallocation from manufacturing to real estate that substantially outpaces structural change in the real economy.
  • Credit-to-value-added diverges sharply. Real estate credit/VA rises steeply with income, while manufacturing credit/VA rises modestly and then declines in high-income countries.
  • Three drivers of the reallocation:
    1. A collateral channel: the elasticity of credit growth to house-price shocks is higher in real estate than in manufacturing, so rising real-estate prices with development disproportionately relax real-estate firms’ constraints.
    2. Rising intangible intensity in manufacturing reduces pledgeability and shifts credit away from the sector.
    3. Liberalization of directed-credit policies (historically biased toward manufacturing/exports, e.g. East Asian miracles, postwar France, UK) is followed by higher total credit but a pronounced reallocation toward real estate.
  • Heterogeneous growth implications. A one-standard-deviation increase in manufacturing credit/GDP predicts +1.1% higher real GDP-per-capita growth over the next five years; the same increase in real-estate credit/GDP predicts −3.5% growth — results robust to controls for development level, real structural change, global shocks, and alternative credit measures.

The composition of credit, not just its level, matters for growth. Financial deepening boosts growth primarily at lower income levels, when it channels resources into manufacturing. At higher income levels, credit increasingly finances real estate, which is associated with weaker subsequent growth. This helps explain the “too much finance” finding and provides empirical grounding for renewed interest in industrial and credit-allocation policies.


Unbalanced Financial Deepening
Authors: Paul W. Dai, Karsten Müller, Emil Verner
From: MIT, National University of Singapore

Collateral, misallocation, and the productivity cost of housing booms: evidence from Canada

Dai, Müller & Verner, above, argue that as economies develop, credit reallocates disproportionately toward real estate, and that reallocation robustly predicts weaker subsequent GDP-per-capita growth. Their framework attributes this to the collateral channel, but they can only identify it indirectly, through cross-country regressions and a model. In this paper, Yuanchen Yang, Flora Lutz, and Lucy Qian Liu supply the missing firm-level micro-evidence for exactly that mechanism inside a single economy.

Yang et al. use a one-period partial-equilibrium model of heterogeneous firms with a Kiyotaki-Moore-style collateral constraint, similarly to Dai et al. above. The model delivers three testable predictions: (i) housing booms raise aggregate investment, (ii) firms with more initial real-estate holdings invest relatively more when house prices rise, and (iii) average industry TFP falls with house prices when real-estate-intensive firms are less productive. For data, the authors use the Canadian Real Estate Association’s MLS Home Price Index and Compustat firm-level data on listed Canadian firms which includes 7,091 firm-year observations, from 2000 to 2023, excluding finance and mining.

Findings

  • Less productive firms hold more real estate. Higher initial tangible-asset ratio is associated with significantly lower productivity. This is the microeconomic reason why Dai et al.’s cross-country regressions find real-estate credit predicts slower growth: the marginal dollar of real-estate-collateralised credit flows, on average, to lower-TFP firms.
  • Housing booms asymmetrically reward tangible-asset-rich firms. A rise in real house prices lowers investment for asset-light firms but raises it for tangible-asset-rich ones. This is precisely the collateral channel Dai et al. posit as one of three drivers of unbalanced financial deepening as confirmed at the firm level.
  • Aggregate productivity drag in tangible-intensive industries. While house prices are on average positively correlated with industry productivity, the relationship turns significantly negative in tangible-intensive industries. This is the micro mechanism that delivers Dai et al.’s headline macro number: real-estate credit expansion → misallocation toward low-TFP firms → lower industry productivity → slower aggregate GDP growth.

Yang et al. extend the correlation to 11 advanced economies (1986–2019), finding a negative lagged house-price / productivity relationship everywhere except Germany, Japan, and the US. The broad geographic pattern echoes Dai et al’s cross-country regressions, suggesting the channel generalizes.

Housing Booms and Productivity Growth
Authors: Yuanchen Yang, Flora Lutz, Lucy Qian Liu
From: IMF

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