QUT

Dr Ruchith Dissanayake

Financial Economist Senior Lecturer, School of Economics and Finance, Faculty of Business and Law, QUT

I study what happens when the future gets harder to read.

How news about government spending, taxes and geopolitical risk moves asset prices, and how firms, banks and households respond.

Explore the research
Profile

About

Ruchith Dissanayake

I am a financial economist at QUT working at the intersection of markets, policy and corporate decision-making. I hold a PhD in Finance from the University of Alberta and was a visiting PhD researcher at the University of California, San Diego. My research examines how firms, investors and households respond when economic, policy and geopolitical conditions become harder to predict.

My work spans asset pricing, corporate finance and macro-finance, with a particular interest in how uncertainty shapes investment, market valuations and real economic decisions. Alongside academia, I maintain an active connection to industry through financial services and advisory work, helping keep my research and teaching grounded in the decisions firms and households actually face.

Research

Papers and grants

Selected publications

Journal (open access)
Journal

Current research

SSRN author page
SSRN

Grants

  • 2026Chief Investigator, Australian Housing and Urban Research Institute (AHURI): financial risk reduction interventions to boost housing supply: policy levers and impacts. $179,207.
  • 2026–27Project lead, QUT Scholarship of Learning and Teaching grant with Catherine Batch: an AI-powered quantitative refresher for MBA students. $7,500.

Research training

Associate supervisor on two completed PhDs (2024, 2026) and supervisor of three completed Honours theses (2022–25). External reviewer for three PhD theses, including one in finance at the Australian National University.

Public writing

Commentary

I write for investors and general readers when research has something to say about a live policy debate.

Shorter takes on research and markets are on Instagram at @dr.ruchith. For media enquiries, contact the QUT media team or email me directly.

MBA and EMBA

Teaching

I teach the quantitative core of QUT's MBA and Executive MBA.

Both units follow the same design: learn the technique, then apply it to a Harvard Business Publishing case with real data in Excel, and defend a recommendation a manager could act on.

  • MBA, EMBAFinancial Management: capital budgeting, risk and return, cost of capital and portfolio optimisation.
  • MBA, EMBAData Analysis and Decision Making: from describing data to multiple regression, with emphasis on causality, omitted variables and the limits of what data can tell a decision-maker.
  • 2018–24International Finance (undergraduate).

Nominated for the 2024 QUT Vice-Chancellor's Award for Teaching Excellence.

Profession and university

Service

  • 2024–Associate Editor, Humanities and Social Sciences Communications (Nature Portfolio)
  • 2024–26Associate Editor, Economic Analysis and Policy
  • 2019–24Founder and Chair, Queensland Corporate Finance Conference (2019, 2022, 2023, 2024)
  • 2025–26Member, Faculty Academic Appeals and Review Committee, QUT
  • 2021–22Member, Faculty Academic Board, Faculty of Business and Law, QUT
  • 2019–20Research Seminar Convenor, School of Economics and Finance, QUT
  • 2017–23Program committee, Financial Management Association Annual Meeting, FMA Asia/Pacific, FMA European Conference, AFAANZ and Academy of International Business meetings
  • OngoingReferee for journals including Journal of Corporate Finance, Journal of Empirical Finance, British Accounting Review, Journal of Business Finance and Accounting, Finance Research Letters and International Review of Economics and Finance
Industry

Practice

BID Capital

Principal and Strategic Advisor

Alongside my academic work, I am Principal and Strategic Advisor at BID Capital, a Brisbane-based mortgage and finance brokerage. The role gives me direct exposure to lending markets, household financial decisions and the way changes in interest rates, credit conditions and economic uncertainty affect decisions in practice.

My focus is on strategy, market insight, risk analysis and business development. Client lending advice and regulated credit activities are undertaken by BID Capital's accredited brokers.

National finalist, New Office of the Year, 2026 Australian Broking Awards

bidcapital.com.au

BID Capital Pty Ltd (ABN 54 669 671 229) is Credit Representative 551902 of Connective Credit Services Pty Ltd, Australian Credit Licence 389328.

Material on this site is general information only. It is not credit assistance or financial, tax or legal advice, and it does not take your circumstances into account. Views expressed here are my own and not those of QUT.

Get in touch

Contact

For research collaboration, seminar invitations, examining or media requests, email is best.

Email
UniversityQUT staff profile
PapersSSRN author page
Instagram@dr.ruchith
Review of Corporate Finance Studies · 13(2) · 2024

The Burden of National Debt: Evidence from Mergers and Acquisitions

Ruchith Dissanayake, Yanhui Wu and Huizhong Zhang · Review of Corporate Finance Studies 13(2): 583–624 · Advance access 27/04/2022 · Open access

The question

Does a rise in government debt hold back corporate acquisitions, and if so, through which channel?

How it works

The paper tests two channels that can operate together.

Government debt-to-GDP rises

Debt substitutability

  1. Investors absorb the extra Treasuries and hold fewer competing securities
  2. High-grade corporate bonds are the closest substitutes, so demand for them falls most
  3. The cost of debt rises for the safest, most creditworthy firms

Fiscal uncertainty

  1. Uncertainty rises about how the budget will be consolidated: taxes, spending or both
  2. The option to wait on irreversible investment becomes more valuable
  3. Firms exposed to fiscal policy uncertainty delay deals
Fewer acquisitions. The deals that proceed use less cash, avoid irreversible targets and are of lower quality.

The evidence

A one-standard-deviation rise in ΔDebt/GDP lowers the probability of making an acquisition

Decrease in acquisition probability, %, as reported in the paper

9.92%
Unconditional probability that a firm makes an acquisition in a given year, the benchmark for the effects above
1981–2016
Quarterly US data on aggregate deal value and volume, and a firm-level panel
Show as table
EstimateHorizonDecrease in probability
Panel regressionNext year1.97%
Panel regressionNext three years3.86%
Instrumented with government spending shocksNext year2.36%

A positive shock to debt-to-GDP narrows the spread between AAA corporate bonds and long-term Treasuries and raises economic policy uncertainty, consistent with both channels. The effect is stronger for firms with high credit ratings or low default risk, and for firms whose stock returns are sensitive to fiscal policy uncertainty: taxes, government spending and entitlement programs. Uncertainty about monetary policy, regulation and trade policy has no effect.

Why it matters

The cost of public borrowing is usually discussed through interest rates and private investment. This paper follows it into the market for corporate control. Earlier work stresses how market frictions hurt financially constrained firms. Here the firms that pull back are large and creditworthy, and they matter enough for government borrowing to weaken the overall takeover market.

Deal quality also falls as debt rises, with lower combined synergies and weaker acquirer announcement returns. The paper links this partly to fiscal uncertainty weakening external monitoring, which lets firms with weaker governance pursue bad deals.

Data and method

Shock
Change in the US federal debt-to-GDP ratio (ΔDebt/GDP)
Aggregate
Local projections (Jordà 2005) on quarterly deal value and volume, 1981–2016
Firm level
Panel regressions of acquisition likelihood with macro, industry-valuation and firm controls
Identification
Instrumental variables using Blanchard–Perotti (2002) government spending shocks
Uncertainty
Firm betas on the Baker, Bloom and Davis (2016) economic policy uncertainty index and its components
Deal terms
Heckman two-stage model, with mutual fund trading pressure as the exclusion restriction

Read and cite

Read the paper (open access)
Dissanayake, R., Wu, Y., & Zhang, H. (2024). The burden of national debt: Evidence from mergers and acquisitions. Review of Corporate Finance Studies, 13(2), 583–624. https://doi.org/10.1093/rcfs/cfac018
Journal of Economic Dynamics and Control · 133 · 2021

Geographic Distribution of Firms and Expected Stock Returns

Ruchith Dissanayake · Journal of Economic Dynamics and Control 133: 104267 · Online 20/10/2021

The question

Does where an industry's firms are located change how risky their stocks are?

How it works

Firms that cluster together share local labour market networks. Information spills over between managers, and wages adjust together when conditions turn. That gives clustered firms a natural hedge that dispersed firms lack.

An aggregate shock hits the economy

Agglomerated industry

  1. Dense local labour networks and coordinated responses among managers
  2. Wages are more procyclical and fall faster in downturns
  3. Cash flows are partly hedged against the shock
  4. Lower cost of equity and lower expected returns

Geographically dispersed industry

  1. Weaker local networks across locations
  2. Wages are stickier through the cycle
  3. Cash flows fall more in recessions
  4. Investors demand a premium to hold the stock

How it is measured

Agglomeration comes from the Ellison–Glaeser (1997) index γ, computed for 4-digit SIC manufacturing industries from 1987 Census employment data. Higher γ means more geographic concentration; γ = 0 means locations look random.

Ellison–Glaeser γ for industries cited in the paper

Higher values mean more geographically concentrated

Firms in the top tercile of γ are agglomerated; the bottom tercile are dispersed. The GDMA factor goes long dispersed and short agglomerated industries, balanced by size. Each stock's exposure, βGDMA, is estimated over a 60-month window, so non-manufacturing stocks can be scored too.

The evidence

The geographic risk premium appears in recessions

Monthly CAPM alpha, %, of value-weighted portfolios sorted on βGDMA, July 1947 to December 2018

  • NBER recessions
  • Expansions
≈15.2%
Annualised CAPM alpha of the high-minus-low geographic risk spread in recessions (1.265% a month, t = 2.25)
≈13.2%
The same spread after the Carhart four-factor model in recessions (1.099% a month, t = 2.00)
0.188%
Monthly CAPM spread in expansions, statistically insignificant (t = 1.02)
Show as table
Monthly CAPM alpha (%)A (low)234GD (high)GD − A
Full sample−0.235−0.0370.0360.0650.1030.338
Recessions−0.7620.0280.2320.2290.5031.265
Expansions−0.163−0.0600.0180.0450.0250.188

Source: Table 5 of the paper. A is the quintile with the lowest βGDMA (least geographic risk); GD the highest.

Industry wage data from 1958 to 2011 confirm the mechanism: wages are more procyclical in agglomerated industries. At the firm level, earnings are more cyclical for high-βGDMA firms. The premium survives excluding microcaps, holds out of sample among non-manufacturing stocks, and is larger among less profitable firms that are more exposed to adverse shocks.

Why it matters

Economic geography is a priced risk. Where an industry's firms locate shapes how its labour costs move over the cycle, and investors price that exposure mainly in recessions, when the hedge is worth the most. The effect may strengthen over time, since fewer Americans now make long-distance moves.

Data and method

Stocks
NYSE, AMEX and Nasdaq common stocks (CRSP), excluding financials and utilities, July 1947 to December 2018
Geography
Ellison–Glaeser (1997) agglomeration index, 4-digit SIC manufacturing, 1987
Factor
GDMA: dispersed minus agglomerated, from six size and geography portfolios, microcaps excluded
Exposure
βGDMA from 60-month rolling regressions
Tests
Quintile portfolio sorts, CAPM and Carhart (1997) alphas, NBER recession split; industry wage panel (NBER-CES)

Read and cite

Read the paper
Dissanayake, R. (2021). Geographic distribution of firms and expected stock returns. Journal of Economic Dynamics and Control, 133, 104267. https://doi.org/10.1016/j.jedc.2021.104267
Working paper

Fiscal News and the Role of Beliefs in Asset Prices

Ruchith Dissanayake · Sole-authored · Draft May 2026 · Results may change in revision

The question

Can stock prices tell us when news about future government spending arrives, and what does that news do to households and markets?

How it works

Government purchases are announced early and delivered slowly, so realised spending is a poor measure of when fiscal news actually lands. Defense contractors' revenues are tied to federal purchases, so their share prices move when expectations about future spending change.

Classify 370+ industries using the national input–output tables

Defense-oriented firms

  1. Industries whose main source of demand is defense purchases
  2. Split into small, medium and large by NYSE breakpoints
  3. Value-weighted portfolio returns each month

Private-sector firms

  1. Industries producing mainly for consumption and investment; exporters excluded
  2. Same three size groups
  3. Value-weighted portfolio returns each month
Defense-minus-private (DMP) spread: a monthly reading of revisions in expected federal spending

Diversifying across industries and size groups keeps firm-specific events out. In 1971Q1 McDonnell Douglas surged on news about its commercial DC-10 aircraft, and in 1999Q4 Raytheon and Lockheed Martin fell on cost overruns and launch failures. Contractor returns spiked in both episodes; the DMP spread barely moved.

Does it measure spending news?

The DMP spread predicts next quarter's unexpected federal, defense and total spending, but not state spending

F-statistic from regressing ARMA(2,1) spending innovations on the lagged DMP spread, 1965Q3–2023Q3, 232 quarters

Show as table
Unexpected change in spendingCoefficient on DMPt−1t-statisticF-statistic
Federal0.0584.3318.55
Defense0.0563.4912.05
Total government0.0273.5712.63
State−0.001−0.580.01

Source: Table 1 of the working paper. Newey–West t-statistics.

State spending is the placebo: defense news should not move it, and it does not. The spread also predicts VAR-identified spending shocks and professional forecasters' errors one quarter ahead, while standard business-cycle indicators cannot predict the spread itself.

What it finds

On average, positive spending news is followed by persistent falls in household consumption and real wages, and marginal tax rates rise over the long run. That pattern fits a negative wealth effect: households anticipate higher future taxes.

The average hides state dependence. When investor sentiment is low, consumption falls sharply after spending news, and the news predicts lower stock returns over one to four years. When sentiment is high, the consumption response is muted and the return predictability disappears. The paper points to beliefs, not only economic slack, as a conditioning variable for fiscal policy.

Data and method

Returns
CRSP non-financial firms (NYSE, AMEX, Nasdaq); Compustat accounting data
Macro
BEA national accounts; Barro–Redlick (2011) marginal tax rates
Validation
Predictive regressions on ARMA spending innovations; comparison with Ramey (2011) defense news, Fisher–Peters (2010) contractor returns, Blanchard–Perotti VAR shocks and SPF forecast errors
Dynamics
Jordà (2005) local projections and IV local projections, quarterly and monthly
State
Baker–Wurgler investor sentiment

Read

SSRN author page

This is a working paper. Comments are welcome by email.
Working paper

Financial Flexibility, Geopolitical Risk, and Corporate Outcomes

Ruchith Dissanayake, Vikas Mehrotra and Yanhui Wu · Evidence from Investment, Profitability, and Default Risk · Draft March 2026

The question

When geopolitical risk rises, does cash on the balance sheet protect a firm, or does it change how the firm behaves?

How it works

Wars, terrorist attacks and political conflicts are sudden and largely outside firms' control, which makes geopolitical risk a cleaner uncertainty shock than volatility or policy indices. Cash gives managers room to act on that uncertainty, and the room cuts both ways.

Geopolitical risk rises (Caldara–Iacoviello index)

Firms with ample cash

  1. Can afford to wait, so they delay irreversible investment more
  2. Scale back production; revenue falls and existing assets sit underused
  3. Costs are sticky, so operating profitability drops further
  4. The cash buffer keeps default risk from rising much

Firms with little cash

  1. Less able to pause and restructure activity
  2. Smaller operating adjustment
  3. More exposed to financial distress
  4. Harder for analysts to forecast

The trade-off

How cash-rich firms respond to a rise in geopolitical risk, relative to other firms

Direction of the estimated effect in the paper's panel regressions

Irreversible investmentFalls more
Operating profitabilityFalls more
Default riskRises less
Analyst forecast errors and dispersionRise less

Decomposing earnings shows the profitability decline comes mainly from lower revenue and production, not from proportional cost cuts. The investment result holds with net working capital, a financial flexibility index and ex-ante cash holdings in place of cash.

Why it matters

Cash is usually read as protection against uncertainty. This paper shows it also changes behaviour: flexible firms act on the option to wait, which shows up in reported earnings as a sharper short-term decline even while their balance sheets stay safer. For investors and analysts, the firms that are hardest to forecast in a geopolitical shock are the ones without that buffer.

Data and method

Sample
Compustat quarterly, US non-financial, non-utility firms, 1985–2019 (ending before COVID-19)
Shock
Caldara and Iacoviello (2021) geopolitical risk index
Flexibility
Top tercile of cash to assets; alternatives: net working capital, Dasgupta et al. (2024) index, Huang–Ritter ex-ante cash
Outcomes
Capital expenditure, operating ROA and its components, Merton distance-to-default, I/B/E/S forecast errors and dispersion
Estimation
Panel regressions with firm and year-quarter fixed effects, two-way clustered errors; local projections for profitability dynamics

Read

This is a working paper. A draft is available on request by email.
Curriculum vitae

Ruchith Dissanayake

Senior Lecturer, School of Economics and Finance, Faculty of Business and Law, QUT · r.dissanayake@qut.edu.au · Updated 16/08/2026

Appointments

  • 2018–Senior Lecturer in Finance, Queensland University of Technology
  • 2017–18Lecturer in Finance, Queensland University of Technology

Education

  • 2012–17PhD in Finance, University of Alberta, School of Business. Advisors: Masahiro Watanabe and Akiko Watanabe
  • 2015Visiting PhD student, University of California, San Diego. Advisor: Valerie Ramey
  • 2010–12MA in Economics and Finance, University of Alberta

Research interests

Asset pricing, international finance and corporate finance.

Publications

  • 2024The Burden of National Debt: Evidence from Mergers and Acquisitions, with Yanhui Wu and Huizhong Zhang. Review of Corporate Finance Studies 13(2): 583–624 (online 2022)
  • 2021Geographic Distribution of Firms and Expected Stock Returns. Journal of Economic Dynamics and Control 133: 104267

Working papers

  • 2026Fiscal News and the Role of Beliefs in Asset Prices
  • 2026Financial Flexibility, Geopolitical Risk, and Corporate Outcomes: Evidence from Investment, Profitability, and Default Risk, with Vikas Mehrotra and Yanhui Wu
  • 2026Banking System Efficiency and Firm Outcomes during Crises, with Yanhui Wu
  • 2026Cultural Anchors and the Heterogeneous Impact of Economic Uncertainty on Housing Returns, with Ama Samarasinghe, Benno Torgler and Yanhui Wu

Grants and awards

  • 2026Chief Investigator, AHURI: Financial risk reduction interventions to boost housing supply: policy levers and impacts. $179,207
  • 2026Project Leader, Faculty Scholarship of Learning and Teaching seed funding, with Catherine Batch. $7,500
  • 2024QUT Early Career Academic Certificate of Appreciation: Excellence in Research Collegiality
  • 2019Finalist, best paper award, FMA Asia/Pacific Conference (Tax Shocks, Political Cycles, and Asset Prices)
  • 2018Semi-finalist, best paper awards, FMA Annual Meeting (Government Spending Shocks and Firm Innovation)
  • 2016Semi-finalist, best paper awards, FMA Annual Meeting (Investment Shocks and Asset Returns: International Evidence)
  • 2016FGSR Profiling Alberta's Graduate Students Award; Scotiabank NFA Registration Award
  • 2012–17University of Alberta Business PhD Award and Scholarship; AIMCo PhD Scholarship in Finance; GRA Rice Graduate Scholarship in Business; Doctoral Students Abroad Funding; Ernst & Young PhD Faculty Fellowship; Faculty grant funding

Presentations

  • 2026Sydney Banking and Financial Stability Conference
  • 2025FIRN Annual Conference
  • 2024FIRN Corporate Finance Meeting; FIRN Annual Conference
  • 2023AFAANZ Conference; Econometric Society Africa Meeting; Econometric Society Australasian Meeting; FIRN Banking and Financial Stability Meeting; Financial Markets and Corporate Governance Conference; Deakin University; University of Melbourne; UNSW
  • 2022American Economic Association Annual Meeting; Australasia Meeting of the Econometric Society; FMA Asia/Pacific Conference; International Risk Management Conference; Australian National University; University of Adelaide; University of Queensland
  • 2021Asian Finance Association Conference; Conference on Law and Macroeconomics; FIRN Annual Conference; FIRN Banking and Financial Stability Meeting; FMA Annual Meeting; Frontiers in International Finance and Banking Conference; French Finance Association (AFFI); International Risk Management Conference; Vietnam Symposium in Banking and Finance
  • 2020Conference on Asia-Pacific Financial Markets; European Finance Association Annual Meeting; Midwest Finance Association Annual Meeting
  • 2019Australian National University; FIRN Annual Conference; FMA Asia/Pacific Conference
  • 2018American Finance Association Annual Meeting; China International Conference in Finance; FIRN Asset Pricing Meeting; Financial Markets and Corporate Governance Conference; Politics, Stock Markets and the Economy Conference; Auckland University of Technology; Macquarie University; Massey University; University of Auckland; University of Melbourne; University of Queensland
  • 2017American Economic Association Annual Meeting; Auckland Finance Meeting; Australasian Finance and Banking Conference; European Economic Association Congress; Midwest Finance Association Annual Meeting; SFS Cavalcade Asia-Pacific; Australian National University; QUT; University of Windsor
  • 2016Auckland Finance Meeting; Australasian Finance and Banking Conference; FMA Annual Meeting; Northern Finance Association Conference; European Economic Association Congress; Southern Illinois University

Own presentations only. Co-authors have also presented joint work at more than twenty further meetings and seminars.

Conference roles

  • Founder, chairQueensland Corporate Finance Conference: 2019, 2022, 2023, 2024
  • Session chairAustralasia Meeting of the Econometric Society (2022); Northern Finance Association (2021); Midwest Finance Association (2017); Australasian Finance and Banking Conference (2016); FMA Annual Meeting (2016)
  • DiscussantMonash Winter Finance Conference (2025); FIRN Annual Conference (2022, 2024); FIRN Asset Management Meeting (2023); FMA Asia/Pacific (2022); AFFI (2021); Asian Finance Association (2019, 2021); Auckland Finance Meeting (2016, 2017); SFS Cavalcade Asia-Pacific (2017); Midwest Finance Association (2017); Australasian Finance and Banking Conference (2016); FMA Annual Meeting (2016)
  • CommitteesAcademy of International Business (2023); FMA Asia/Pacific (2017, 2022); FMA Annual Meeting (2017, 2018, 2019, 2021, 2022); AFAANZ (2018); FMA European Conference (2017)

Service

  • 2024–Associate Editor, Humanities and Social Sciences Communications (Nature Portfolio)
  • 2024–26Associate Editor, Economic Analysis and Policy
  • 2025–26Faculty Academic Appeals and Review Committee, QUT
  • 2021–22Faculty Academic Board, Faculty of Business and Law, QUT
  • RefereeJournal of Corporate Finance, British Accounting Review, Journal of Business Finance and Accounting, Journal of Empirical Finance, Economic Analysis and Policy, Economics Letters, Finance Research Letters, International Review of Economics and Finance, Japan and the World Economy, Australian Journal of Management, Papers in Regional Science, Financial Innovation

Supervision

  • PhDAssociate supervisor: Jiayi Yang (2026); Richard Colthurst (2024). PhD committee chair: Abdullah Khojah
  • ExaminingExternal reviewer: Ang Li, PhD in Finance, ANU (2024); Emma Joenpolvi, PhD in Marketing (2025); Pasit Sararueangpong, PhD in Marketing (2025)
  • HonoursKameron Nimmo (2025); Jorge Gallo Livia (2024); Jason Morcom (2022)

Teaching

  • 2018–QUT: Data Analysis and Decision Making (MBA, EMBA); Financial Management (MBA, EMBA); International Finance (undergraduate)
  • 2015–16University of Alberta, Instructor: Investment Principles; Introduction to Finance
  • 2013–14University of Alberta, Teaching Assistant: Investment Principles; Advanced Portfolio Management; International Finance (undergraduate and MBA)

Media

  • 02/09/2026Who really loses from the SMSF borrowing ban? Firstlinks (Morningstar), with Ama Samarasinghe
  • 10/2022Sri Lankans should never be complacent about the status quo. LMD
  • 07/2022Rein in inflation. LMD
  • 05/06/2022The need to privatize state-owned enterprises. The Sunday Times Sri Lanka
  • 15/05/2022Inflation has sky-rocketed. The Sunday Times Sri Lanka
  • 08/05/2022Investors need confidence that Sri Lanka is a safe choice for investment. The Sunday Times Sri Lanka

Memberships

American Economic Association, American Finance Association, Financial Management Association International, European Finance Association and Northern Finance Association (all since 2016); Econometric Society (since 2021).
Working paper

Banking System Efficiency and Firm Outcomes during Crises

Ruchith Dissanayake and Yanhui Wu · Draft July 2026 · Results may change in revision

The question

When a crisis starts outside the financial system, does the efficiency of a country's banks decide how hard its firms cut back?

How it works

COVID-19 hit firms' cash flows, not banks' balance sheets, and sent firms to their banks for liquidity all at once. That makes it a clean test of whether the banking system itself, rather than any single lender, shapes how firms come through a shock.

Banking system efficiency (BSE) index: interest margins, lending–deposit spreads, overhead costs, non-interest income and profitability, combined by Bayesian principal components on rolling five-year windows

Short-term liquidity

  1. Efficient systems expand short-term credit during the crisis
  2. Liquidity reaches firms broadly, regardless of collateral
  3. Firms can fund immediate needs without cutting investment as much

Long-term credit and pricing

  1. Long-term debt goes selectively to firms with more tangible assets
  2. Pricing is more risk-sensitive: underperforming firms pay more
  3. High-performing firms are relatively protected
Smaller investment declines in 2020–21, concentrated among firms that depend on bank finance, with credit reallocated toward stronger firms

The measure

Banking system efficiency varies widely, and not only with income

Average BSE index, 2011–2019, for the 55 countries in the firm sample. Higher is more efficient. Hover for each country.

Show as table
CountryBSE 2011–19BSE 2020–21Firm-years 2011–19

Source: Table 2 of the working paper.

The first component explains about 45% of the variation in the five banking characteristics. It loads negatively on margins, spreads, overhead costs and bank profitability: in more competitive systems, efficiency compresses bank rents. Because each year's index uses only the previous five years of data, it contains no information from the crisis itself.

What it finds

In normal years, the index has no meaningful effect on investment. In 2020 and 2021, firms in higher-efficiency systems cut capital investment significantly less. The effect is concentrated among firms and industries that rely on bank debt, which points to credit supply rather than differences in investment demand.

The result holds with country × year fixed effects, which absorb fiscal and monetary support and any other country-wide response to the pandemic, and with the index measured two years before the crisis. The IMF's financial institutions efficiency index does not predict the same investment responses. Bank for International Settlements aggregate credit data also show a larger credit expansion in more efficient systems.

Why it matters

How a firm comes through a crisis depends on its own balance sheet and also on the banking system around it. Efficient systems do two things at once: they keep liquidity flowing and they discipline long-term credit. The result is a smaller aggregate investment decline and a reallocation of credit toward more productive firms.

Data and method

Banking
World Bank Global Financial Development Database; index available for more than 150 countries
Firms
Compustat Global, listed non-financial firms in 55 countries, 2011–2021 (about 231,000 firm-years)
Crisis
Indicator for 2020 and 2021; BSE lagged at least one year
Identification
Differential exposure to bank finance (Rajan–Zingales), country × year fixed effects; pre-trend check on residual investment
Mechanisms
Short- and long-term debt, asset tangibility, cost of debt, profitability and firm value

Read

This is a working paper. A draft is available on request by email.
Working paper

Cultural Anchors and the Heterogeneous Impact of Economic Uncertainty on Housing Returns

Ruchith Dissanayake, Ama Samarasinghe, Benno Torgler and Yanhui Wu · Draft May 2026

The question

Does economic uncertainty hold back house prices, and does national culture change how much?

How it works

Uncertainty here is ambiguity about the distribution of outcomes, not measurable risk. Housing is a large, illiquid, long-horizon purchase that households cannot easily hedge, so ambiguity pushes them toward precautionary saving instead.

Economic uncertainty rises (World Uncertainty Index)
Households delay committing to illiquid housing, and housing returns fall over the following 4 to 12 quarters

Culture that amplifies

  1. Individualism: weaker informal risk sharing between families and communities
  2. Long-term orientation: uncertainty disrupts long-run saving and investment plans more

Culture that dampens

  1. Work ethic: confidence in future income and disciplined saving
  2. Offsets the effect at 8- and 12-quarter horizons

The evidence

Uncertainty lowers housing returns, more so in individualistic countries

Change in cumulative housing return, percentage points, for a one-unit rise in the uncertainty index, 1995Q1–2019Q4

  • Average effect, all countries
  • Additional effect, high-individualism countries
−6.3 pp
Turkish housing returns over four quarters after the 2013 Gezi Park protests, relative to an Eastern European control group
−11.5 pp
The same gap over eight quarters
3.8–12.6 pp
Reduction in housing returns in high long-term-orientation countries, across horizons
Show as table
HorizonAverage effect (pp)Additional, high individualism (pp)
4 quarters−1.9−3.8
8 quarters−3.8−4.2
12 quarters−5.5−6.7

Source: Table 3 and the individualism results of the working paper. All average effects are significant at the 1% level.

Turkey's economy kept growing through 2013, so the Gezi Park protests raised uncertainty without a matching downturn. That makes the episode a natural experiment. Instruments based on the timing of executive elections point the same way, and the effect is larger again over the longer 1970–2019 sample.

Why it matters

Housing is most households' largest asset and a channel from uncertainty into wealth, consumption and credit. The same uncertainty shock does not land the same way everywhere: culture shapes how households respond, so policy aimed at steadying housing markets needs to account for more than macroeconomic fundamentals.

Data and method

Housing
BIS real residential property price indexes; 4-, 8- and 12-quarter forward returns; 41 countries
Uncertainty
World Uncertainty Index (Ahir, Bloom and Furceri 2022), text-mined from Economist Intelligence Unit reports
Risk control
Volatility of each country's real estate sector stock returns
Culture
Hofstede individualism and long-term orientation; work ethic from the European Values Study and World Values Survey
Identification
Country and time fixed effects; executive-election timing instruments; difference-in-differences around the Gezi Park protests

Read

Read on SSRN