Spatial Spillovers and Labor Market Dynamics: Village Financial - PowerPoint PPT Presentation

Spatial Spillovers and Labor Market Dynamics: Village Financial Interventions in Thailand CEPR/IGC/ILO/UNIGE Conference on Labour Markets in Developing Countries Daniel Ehrlich Robert M. Townsend Massachusetts Institute of Technology May 9, 2019 Daniel Ehrlich, Robert M. Townsend (Massachusetts Institute of Technology) Spatial Spillovers and Labor Market Dynamics: Village Financial Interventions in Thailand May 9, 2019 1 / 42

Introduction Motivation Motivation How does one evaluate the general equilibrium, macro e ff ects of scaled-up village-level RCTs and interventions? Yale Research Initiative on Innovation and Scale: “While evaluation techniques for pilot-scale programs are well developed, complexities arise when we contemplate scaling up interventions to create policy change.” Conceptual Framework: Previous Literature: using micro RCT data embedded in macro models to compute general equilibrium counterfactuals (e.g. Buera Kaboski and Shin 2017) Why can’t we use the approach in the previous literature? With imperfect labor markets, cannot jump to frictionless GE. In developing countries, such frictions abound - Buera, Kaboski, and Townsend (2018). Our Approach: document and understand the e ff ects of an already scaled-up program Daniel Ehrlich, Robert M. Townsend (Massachusetts Institute of Technology) Spatial Spillovers and Labor Market Dynamics: Village Financial Interventions in Thailand May 9, 2019 2 / 42

Introduction Motivation Preview of Results What we find in Thai village census data: Own credit e ff ect on village level wages Interesting wage dynamics, over time Spillovers from neighboring villages Greater impact of own-e ff ect on more isolated villages Tension: retain what we know of within village economies but aggregate up to get market clearing wages that allows these with spatial patterns. Daniel Ehrlich, Robert M. Townsend (Massachusetts Institute of Technology) Spatial Spillovers and Labor Market Dynamics: Village Financial Interventions in Thailand May 9, 2019 3 / 42

Introduction Program Overview Program Overview Thailand’s “Million Baht Village Fund” program: Created village banks in almost 80,000 villages in 2002 1.5% of Thailand’s GDP Each bank was endowed with 1 million Baht (around $ 24,000) → quasi-natural variation in credit per household at the village level Village size is exogenous Program was unexpected Daniel Ehrlich, Robert M. Townsend (Massachusetts Institute of Technology) Spatial Spillovers and Labor Market Dynamics: Village Financial Interventions in Thailand May 9, 2019 4 / 42

Introduction Previous Literature Within Village E ff ects of Micro Finance What we know and distinguishing short run and long-run. Kaboski and Townsend (2012): Increased total short-term credit, consumption, agricultural investment, and income growth but decreased overall asset growth Increased wages Not a statistically significant e ff ect on occupation Fulford (2011), India, bank placement: Initial boom in consumption and poverty reduction; eventual decrease in consumption, rise in poverty Banerjee, Breza, Duflo and Kinnan (2015): 6 years out, benefits for pre-existing “gung-ho entrepreneur”, but not “reluctant entrepreneurs” Daniel Ehrlich, Robert M. Townsend (Massachusetts Institute of Technology) Spatial Spillovers and Labor Market Dynamics: Village Financial Interventions in Thailand May 9, 2019 5 / 42

Introduction Previous Literature Initial Structural Models Kaboski and Townsend (2011)’s model includes: Precautionary liquid savings to smooth uninsured income shocks (will be included in our model) Limited borrowing due to financing constraints, as a function of permanent income (constraints key in our model) Investment which is discrete with stochastic opportunities, common real return (investment smooth in our model) Daniel Ehrlich, Robert M. Townsend (Massachusetts Institute of Technology) Spatial Spillovers and Labor Market Dynamics: Village Financial Interventions in Thailand May 9, 2019 6 / 42

Introduction Previous Literature New ingredients and results not in original models Banerjee, Breza, Townsend, and Vera-Cossio (2018): Large heterogeneity in terms of underlying household productivity TFP estimated with pre-intervention data Large increase post intervention in profits, and assets used in production, especially non-agriculture business, but not for the lower quartiles of productivity Our model has TFP heterogeneity as key ingredient across villages (and will be also within) Pawasutipaisit and Townsend (2011), Samphantharak and Townsend (2017): Average returns are highly persistent over time (our model allows for this, TFP currently fixed) Village committee did not allocate funds by productivity (our model does not encompass this) Daniel Ehrlich, Robert M. Townsend (Massachusetts Institute of Technology) Spatial Spillovers and Labor Market Dynamics: Village Financial Interventions in Thailand May 9, 2019 7 / 42

Introduction Previous Literature Alternative Commodity Spaces Paweenawat and Townsend (2018): Documented villages more open to capital than labor (we keep this) Multiple goods and trade Breza and Kinnan (2018): Multiple goods, tradable and non-tradable Our model has one good. Documenting commodity output, consumption, and input flows in Thailand: Burstein, Hanson, Tian, and Vogel (2018): prices respond more in non-tradable than tradable sectors to immigration Most goods at the village level are tradable - Paweenawat and Townsend (2018) Also Paweenawat and Townsend (2018): no responses in village imports and exports due to Village Fund Daniel Ehrlich, Robert M. Townsend (Massachusetts Institute of Technology) Spatial Spillovers and Labor Market Dynamics: Village Financial Interventions in Thailand May 9, 2019 8 / 42

Introduction Previous Literature Across Village Perspective, E ff ects of Micro Finance Bryan, Chowdhury and Mobarak (2017): Migration subsidy → outflow of labor Increased wages for those left in village (big part of our model) Lagakos, Waugh, Mubarak (2018): Substantial gains to migration for the low income, low asset households (also in our model) Daniel Ehrlich, Robert M. Townsend (Massachusetts Institute of Technology) Spatial Spillovers and Labor Market Dynamics: Village Financial Interventions in Thailand May 9, 2019 9 / 42

Empirical Motivation Data Data Thailand’s Community Development Department (CDD) panel: Bi-annual village-level survey 1986 - 2011 Includes average village daily wages and village population Measurement error in population levels Does not have data on migration flows between villages GIS data of Thailand’s road network: Used to construct bu ff er zones using travel time and travel distance Daniel Ehrlich, Robert M. Townsend (Massachusetts Institute of Technology) Spatial Spillovers and Labor Market Dynamics: Village Financial Interventions in Thailand May 9, 2019 10 / 42

Empirical Motivation Data Figure: Map of Villages and Road Network Daniel Ehrlich, Robert M. Townsend (Massachusetts Institute of Technology) Spatial Spillovers and Labor Market Dynamics: Village Financial Interventions in Thailand May 9, 2019 11 / 42

Empirical Motivation Empirical Results Result 1: Baseline e ff ect of Credit on Wages We run the reduced form regression y it = β Credit i ∗ Post t + φ i + φ t + 󰂄 it (1) where y it is wage in village i at time t Credit i is equivalent to 100 / NoHouseholds i , 2001 , the inverse of the number of households in village i in 2001 Post t is a dummy equal to 1 if t ≥ 2003 φ i is the village fixed e ff ect φ t is the time fixed e ff ect Daniel Ehrlich, Robert M. Townsend (Massachusetts Institute of Technology) Spatial Spillovers and Labor Market Dynamics: Village Financial Interventions in Thailand May 9, 2019 12 / 42

Empirical Motivation Empirical Results Result 1 Table: Microfinance and Wages Baseline (1) (2) (3) (4) (5) (6) VARIABLES Wage Wage Wage Log Wage Log Wage Log Wage Credit i ∗ Post 1.495*** 1.508*** 1.195*** 0.00997*** 0.0114*** 0.00996*** (0.221) (0.202) (0.176) (0.00197) (0.00140) (0.00121) Constant 38.70*** 3.587*** (0.187) (0.00280) Observations 432,783 432,783 432,783 432,783 432,783 432,783 R 2 0.790 0.831 0.851 0.861 0.894 0.906 Number of Villages 39,628 39,628 Year FE YES NO NO YES NO NO Village FE YES YES YES YES YES YES Prov-yr FE NO YES NO NO YES NO Amphoe-yr FE NO NO YES NO NO YES Drop Outliers YES YES YES YES YES YES This table reports the results of equation 4 on wages. Standard errors clustered at tambon-level throughout. *** p < 0.01, ** p < 0.05, * p < 0.1 Daniel Ehrlich, Robert M. Townsend (Massachusetts Institute of Technology) Spatial Spillovers and Labor Market Dynamics: Village Financial Interventions in Thailand May 9, 2019 13 / 42

Empirical Motivation Empirical Results Result 2: Dynamic e ff ect of Credit on Wages We run the regression 2009 󰁜 y it = β t Credit i ∗ φ t + φ i + 󰂄 it (2) t =1986 where Credit i is interacted with the time e ff ect Daniel Ehrlich, Robert M. Townsend (Massachusetts Institute of Technology) Spatial Spillovers and Labor Market Dynamics: Village Financial Interventions in Thailand May 9, 2019 14 / 42

Empirical Motivation Empirical Results Result 2 Figure: Event Study of Credit on Wages with Prov-yr FE Daniel Ehrlich, Robert M. Townsend (Massachusetts Institute of Technology) Spatial Spillovers and Labor Market Dynamics: Village Financial Interventions in Thailand May 9, 2019 15 / 42