Policy Uncertainty in Hybrid Regimes Evidence from Firm-level Surveys

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Policy Uncertainty in Hybrid Regimes Evidence from Firm-level Surveys Tom Kenyon (World Bank) Megumi Naoi (UCSD)

Why are we interested? Economics literature claims policy uncertainty impedes investment & growth (Brunetti et al. etc.) Surveys show uncertainty appears to matter more to firms than macroeconomic instability, taxation etc. Existing literature uses survey data on uncertainty as a proxy of for actual level of policy instability. But what does policy uncertainty mean? Can we trust the data? Can we say what causes policy uncertainty?

Our Contribution We identify polity and firm-level sources of economic and regulatory policy uncertainty using World Bank firm-level survey data We develop a method for identifying and controlling for firm-level reporting biases in polities with limited freedom of speech

Principal Data Source World Bank-EBRD BEEPS data: around 20,000 firms in 24 transition economies (1999, 2002, 2005) Main variable of interest: To what extent is economic and regulatory policy uncertainty is an obstacle to the operation and growth of your business? 0= No obstacle, 1= Minor obstacle, 2= Moderate obstacle, 3= Major obstacle

The Puzzle Democracy Stock and Policy Uncertainty.5 1 1.5 2 2.5-500 0 500 (mean) polity4_imp_depr1 0 20 40 60 80 perc_c218m _23-500 0 500 Democracy Stock using Polity4_imp with 1% depreciation rate Y axis: mean score for policy uncertainty variable Y axis: percentage of firms that responded 2= Moderate obstacle, 3= Major obstacle

Explanations? Increasing uncertainty as endemic to democratization (Hirschman, Przeworski)? Or, the effect of simultaneous economic and political transitions (McDermott)? Or, a figment of the data: the effect of exclusion, suppression and lack of anchoring?

How might we model firms responses? Y (firm s response) = Y(objective) + Y(subjective) + ε Country-level Firm-level Actual level of policy uncertainty Perceived/reported level of uncertainty Immeasurable/lack data Volatility in economic policy Political regimes Electoral polarization Freedom of expression and press Culture, risk-taking attitudes, etc. Sector Ownership Exporters Asset Specificity Manager s level of education [information] Firm age, ownership (foreign vs. domestic) [basis for comparison] Manager s personality, gender, experience, nationality

Macro-Politics & Policy Uncertainty Hypothesize that policy uncertainty is related to nature of elite contestation in hybrid regimes: Expect reported uncertainty to be lower when incumbent stays in office Expect reported uncertainty to be higher when contestation is programmatic as opposed to personalized Data on incumbency from Hale (2005) and media reports Data on political competition from media reports and expert opinion (Freedom House etc.)

Main Results

Main Results (controlling for economic policy volatility)

Other Results Reported level of uncertainty does not systematically differ between foreign vs. domestic firms. More established firms express greater concern over policy uncertainty; but sector and asset specificity have no significant impact Privatization does not have systematic effects on reported level of uncertainty

But - Beware Potential Biases! Anchoring: respondents genuinely mean different things - differential item functioning (DIF) solution: use vignettes to anchor responses (King et al. 2003) Exclusion: respondents don t answer sensitive questions missing data bias solution: triangulate using proxies (Berinsky 2002) Suppression: respondents deliberately give misleading replies (out of fear etc.)

Identifying Suppression Bias Select politically sensitive questions in BEEPs (tax evasion, policy uncertainty, quality of government service) Regress firms subjective responses on objective outcome-based proxies, controlling for firm level/managerial attributes Correlate residuals with measures of press freedom & civil liberties

For example suppose there is suppression bias 0 20 40 60 80 perc_c218m_23-500 0 500 Democracy Stock using Polity4_imp with 1% depreciation rate Without suppression linear relationship?

Matching subjective & objective data Subjective variable Percent sales declared for tax purposes (i.e., tax evasion) Objective variable Size of informal economy (Schneider) Business licenses as obstacle to investment Obtaining licenses (days) (DB) Judiciary as obstacle to investment Enforcing contracts (days) (DB) Electricity as obstacle to investment Percent electricity losses during transmission (WDI)

Suppression Bias- Residuals contract electricity residualsbeepsinformality -.6 -.4 -.2 0.2 -.6 -.4 -.2 0.2 informality license 20 40 60 80 20 40 60 80 Graphs by indicator pressfreedom2004 Remember: if residuals are randomly distributed along the zero line, there is no systematic suppression bias. Positive relationship would indicate expected bias.

Residuals & Political Environment Civil Liberties Press Freedom Informality 0.16 (0.52) 0.19 (0.44) Contract 0.63** (0.00) 0.46* (0.05) License -0.05 (0.81) -0.24 (0.33) Electricity -0.01 (0.97) -0.01 (0.95)

To Recap Reported policy uncertainty higher in hybrid regimes; positively associated with programmatic incumbent turnover No clear evidence of suppression bias: firms in authoritarian regimes can be over critical Inverted U-shaped relationship may be genuine, though cannot rule out other biases Better educated managers provide more objective assessments of IC constraints

What s Next? More systematic coding of programmatic vs. personalized competition. Take into account time between surveys and elections (daily data) Apply this objective-subjective matching to other issue areas (quality of government, property rights protection) The role of information, such as media.