Credit and Productivity Background material for DIA 2009

Roadmap Stylized Facts Financial development and TFP –Analytical discussion –Empirical evidence Macroeconomic volatility and TFP –Analytical discussion –Empirical evidence Ex post volatility Ex ante volatility Final remarks

Roadmap Stylized Facts Financial development and TFP –Analytical discussion –Empirical evidence Macroeconomic volatility and TFP –Analytical discussion –Empirical evidence Ex post volatility Ex ante volatility Final remarks

Stylized Facts

Stylized Facts (cont.) Correlation TFP and FD: LAC=0.80; Asia=0.54

Stylized Facts (cont.)

Stylized Facts (cont)

Stylized Facts (cont.)

Stylized Facts (cont)

Roadmap Stylized Facts Financial development and TFP –Analytical discussion –Empirical evidence Macroeconomic volatility and TFP –Analytical discussion –Empirical evidence Ex post volatility Ex ante volatility Final remarks

Financial Development and TFP Literature on financial development and TFP growth goes as far as Bagehot (1873) and Schumpeter (1912) –Financial markets promote efficient capital reallocation across productive units Hsieh and Klenow (2007), Restuccia and Rogerson (2007), Buera and Shin (2008), Buera et al (2008) point in a similar direction.

Financial Development and TFP Examples of the channels: –Collateral constraints limit entrepreneurship –Financial underdevelopment limits the possibility of entering in highly productive sectors with high fixed costs –Credit market imperfections reduce long term investments (prod. enhancing) vis a vis short term ones

Financial Development and TFP Empirical evidence: –Cross country is abundant (Beck et al, Levine and Servos, Rioja and Valev, Acemoglu, Aghion and Zilibotti, …). –Sectoral level studies focus more on channels (FD vs elasticity of investment to GDP, FD and sensitivity of R&D expenditure to shocks, firm growth) and less on the final impact (TFP).

Financial Development and TFP We add: –Sectoral data: impact of credit availability on TFP –Firm level data: Survey data + Colombia country study

Sector Level Evidence: TFP Estimation Unido Dataset: panel 77 countries, 26 manufacturing sectors, annual data Compute series of capital stock using the perpetual inventory method. (Caselli 2005) Assume Cobb-Douglas technologies:

Sector Level Evidence: TFP Estimation (cont.) TFP: Regression residual TFP1: Fixed-cost shares TFP2: Industry-specific cost shares (Fleiss 2008, Bernanke and Gurkaynak, 2001)

Sector Level Evidence: TFP Estimation (cont.)

Sector Level Evidence: Methodology Estimation Equation (1) Estimation Equation (2)

Sector Level Evidence: Results

Sector Level Evidence: Results (cont.)

Firm Level Evidence: WBES Using the WBES we construct measures of TFP for firms in 54 developing countries (17 LAC) We construct three measures of TFP based on cost shares and a prod function including labor, capital and intermediate inputs. –Cost shares are the same across countries and industries (TFP) –Cost shares are the same across countries but differ across industries (TFPj) –Cost shares differ across countries and industries (TFPij)

WBES TFP Estimations

WBES: Access to credit

Marginal impact of access to credit line Regression: TFP(ij) = f(export, size, access, size*access, CI-FE) Instrument by: past firm growth, share of firms with access in cluster, share*size *** **

Roadmap Stylized Facts Financial development and TFP –Analytical discussion –Empirical evidence Macroeconomic volatility and TFP –Analytical discussion –Empirical evidence Ex post volatility Ex ante volatility Final remarks

Macroeconomic Volatility and TFP – Some Related Literature Crisis, or ex-post volatility I: Recent literature suggests a close connection between crisis and TFP performance: –Calvo et al (2006): Phoenix miracles: Collapse in TFP performanceCollapse in TFP performance –Fernandez Arias et al (2007): TFP seldom recovers to trend –Cerra-Saxena (2007): output does not recover to pre-crisis trend levels Periods of financial crisis are associated with large RER depreciation and RER volatility: –Calvo et al (2004): 63% of large RER depreciations in EMs associated to Sudden Stops –Calvo et al (2006): RER volatility (relative price of tradables vis- à-vis non-tradables) increases with Sudden Stops

Macroeconomic Volatility and TFP: sector level evidence

Macroeconomic Volatility and TFP – Some Related Literature Crisis, or ex-post volatility II: Connection between crisis and productivity through credit markets: –Caballero et al (1994): The now standard view of recessions: A cleansing effect –Barlevy (2003): If credit frictions exist, there could be “uncleansing” effects –Efficient but credit-constrained firms with loose connections to credit markets (or little collateral) could be wiped out, leaving larger but less efficient incumbents in the market –This connection between macroeconomic volatility, credit markets and TFP is what we are working on at the firm level for the case of Colombia.case of Colombia

Macroeconomic Volatility and TFP – Some Literature Exposure to frequent crises and large RER fluctuations also raises ex-ante volatility issues: –Calvo (2005): Greater price volatility increases the profitability of more malleable, less productive technologies –Goldberg (2001): Exchange rate volatility affects the share of foreign direct investment in total investment –We take from Calvo the idea that price volatility conspires against the choice of more productive technologies, and from Goldberg the idea that volatility affects the composition of investment, and ask: –Can volatility affect the sectoral allocation of investment away from what TFP differences would indicate?

Ex-ante Volatility – How does volatility introduce distorsions in investment allocation? Where : Investment ratio, country j sector i over investment country j :Tfp ratio, country j sector i over Tfp country j. : Measure of volatility in country j : Country time and Industry time fixed effects

Relationship Between Investment Ratio and TFP ratio: An Example Consider the case of a 1 period model in which a firm decides on investment in two activities with different productivity levels

Relationship Between Investment Ratio and TFP ratio: An Example (i.e, investment in activity 1 over total investment )

I. Pooled OLS Dependent Variable: Investment Ratio t-1

II. IV-Panel Note 1. According to Exogeneity test (C and Hansen J statistic) we can consider Tfp to be exogenous, in each of the eight models. Note 2. However, due to perpetual inventory methodology used to construct the capital series which involves past Investment values, we could think if Investment ratios exhibit enough persistence, it could influence the Tfp path, that is why we conduct an IV-Panel regression. t-1

Marginal Effect (Different Volatility Levels) Model (4)

IV. Dynamic Panel

Systemic Sudden Stops: Total Factor Productivity in EM Collapses & the US Great Depression Collapses in EM Economies CollapseRecovery t-2t-1tt+1t+2 GDP TFP GDP US Great Depression CollapseRecovery GDP TFP GDP

Case study: Colombia We use plant level data to estimate TFP and combine this data with a sectoral level data base to identify access to finance (firm level panel 1995 – 2005). Our general questions refer to: –Relationship between productivity and crisis/volatility at the firm level, analyzing the role played by credit constraints. Does credit access help smooth shock? –Relationship between entry-exit and firm productivity. Is there a cleansing effect of crisis/volatility? Does credit play a role in the way that crisis affect firms with different productivities?

Case study: Colombia We estimate regressions of the sort to estimate the impact of access to credit on productivity in general and during crisis: We do this at a firm level and at a sectoral level

Case study: Colombia To estimate the impact of access to finance on firm survival: On entry at a sectoral level