Relevance of Today s Paper to Tanzania

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2 Relevance of Today s Paper to Tanzania TZ has more FDI than Ethiopia (24% in Census of Industrial Production 2013 vs 18% in Ethiopia) Moreover, 68% of foreign firm entered TZ s mfg sector since 1998 So, the potential for learning from foreign firms in TZ is real We worked with NBS to develop a technology transfer module that has been implemented by NBS as part of the most recent ASIP Data is currently being cleaned by NBS We will be analyzing the data over the next several months

3 Foreign Direct Investment and Knowledge Diffusion in Poor Locations: Evidence from Ethiopia Girum Abebe (EDRI, Ethiopia), Margaret McMillan (Tufts), Michel Serafinelli (Toronto)

4 The research questions To what extent is the productivity of domestic plants affected by foreign direct investment (FDI)?

5 The research questions To what extent is the productivity of domestic plants affected by foreign direct investment (FDI)? Can domestic plants assimilate knowledge from (superior) foreign plants through observation, imitation and interaction?

6 The research questions To what extent is the productivity of domestic plants affected by foreign direct investment (FDI)? Can domestic plants assimilate knowledge from (superior) foreign plants through observation, imitation and interaction? (new look at quite old questions)

7 Motivation Productivity gaps large between developed and developing countries; FDI could be powerful tool for reducing them Attracing FDI key element of Ethiopian governments industrial policy (also other countries) Previous literature effects not well identified (Handbook DevEC, Harrison and Rodriguez-Clare 2010) Key question is whether knowledge assimilated through observation, imitation and (formal and informal) interaction Similarity between research on FDI spillovers and that on agglomeration advantages (e.g. Greenstone, Hornbeck & Moretti 2010) Our research design exploits geograpic location of FDI

8 This Paper Uses insights from literature on agglomeration to identify causal impact of FDI on domestic plant prody Quantify magnitude of spillovers from FDI using plant-level panel data from Annual Census of Manufacturers Production functions allow total factor productivity (TFP) of domestic plants to depend on presence of large greenfield foreign plant in the district Two research designs addressing issue that district chosen by FDI likely different from average RD1: planned vs actual FDI and RD2: exploits government assignment of land Mechanisms: Technology Transfer survey designed by us

9 Preview of Results over 3 yrs starting with yr of opening, 0.3-standard-deviation increase in TFP in treated domestic plants knowledge transfer through (i) labor flows (ii) learning by observation (iii) customer/supplier relationships (consistent with Serafinelli 2017; Fons-Rosen 2012; Javorcik 2004) foreign plants attract new economic activity Some evidence of increased within firm employment, no changes in wages similar results with RD 1 & 2 (despite different potential omitted variables biases)

10 Outline A Simple Model Data and Descriptive Stats Estimation and Main Evidence Robustness, and Further Evidence

11 Consider a domestic plant j s optimization problem: maxf (A, L) wl L nationally traded good whose price normalized to 1; L: labor; w: wage [see paper for more general framework] A = A(p) p: geographical, temporal and economic proximity to FDI (Rosenthal and Strange 2004, Greenstone Hornbeck and Moretti 2010) FDI spillovers: A/ p > 0

12 Let L denotes the optimal level of labor given wage π = f [A(p), L (w (p))] w (p)l (w (p)) totally differentiate dπ dp = f A A p + w p [ L w ( f L w ) L ] If all domestic plants wage takers and labor paid MP dπ dp = f A A p w p L

13 Outline A Simple Model Data and Descriptive Stats Estimation and Main Evidence Robustness, and Further Evidence

14 Data Central Statistical Agency (CSA) Large and Medium Scale Manufacturing Establishment Census; link up plants for to estimate TFP regressions [Descriptives Sample, Descriptives ETH Economy] In principle, any formal manufacturing plant with L 10 that uses electricity forms part of target population ( ) Feb 2014 technology transfer survey module implented by CSA with LMSM Census June 2016 we visited several plants [Pictures] In-depth interviews with EIC, Ministry of Industry, managers at foreign & domestic plants Restricted administrative data from Ethiopian Investment Commission (EIC)

15 Table: Size, performance and technology indicators by ownership type (2013) (1) (2) (3) (4) Full Sample FDI Domestic p-value of diff. (2)-(3) Number of workers Value added per worker Percent of output sold to FDI (%) Percent of plants that export Percent share of export in total sales Conducted R & D in the last three years Hold internationally recognized patent Use technology licensed from abroad Number of observations 1, ,398 Note: Author s compilation based on CSA census and FDI survey module

16 Outline A Simple Model Data and Descriptive Stats Estimation and Main Evidence - RD1: Actual vs Planned FDI Investments - RD2: Not enough time - Survey Module Evidence Robustness, and Further Evidence

17 Outline A Simple Model Data and Descriptive Stats Estimation and Main Evidence - RD 1: Exploiting assignment of land by Gov t - Survey Module Evidence - RD2: Actual vs Planned FDI Investments Robustness, and Further Evidence

18 Actual vs Planned FDI Investments treated district: where foreign plant actually invested control district: location in which foreign plant in same industry and around same time, applied for a license, got approval but then did not produce during the period of 1-4 years

19 "Currently 2 out of 3 potential FDIs are not realized. Even though a One Stop Shop service is operational its record is mixed. Bureaucratic hurdles continue to affect project implementation [...]. Further research is needed to identify those factors that facilitate the conversion of successful FDI in Ethiopia" (World Bank, 2015) similar discussion in and Chen, Geiger & Fu 2015 Foreign currency shortages and financing issues also sometimes cited (Altenburg, 2010; U.S. Department of Commerce 2017; Moller & Wacker 2015) [Descriptives]

20 ln(y pidrt ) = β K ln(k pidrt ) + β M ln(m pidrt ) + β L ln(l pidrt ) + +δ1(opening ) p + κ1(τ 0) t + ϕ(1(opening ) p 1(τ 0) t ) +α p + µ it + Trend rt + ε pidrt p references plant, i industry, d district, r region, and t year identifying assumption: domestic plants in districts where FDI production delayed form valid counterfactual, after conditioning on plant FE, industry by year FE, etc [Sample of FDI Openings]

21 Table: Plant Characteristics by Treatment Status, One Year Prior to a FDI Plant Opening Treatment Control p-value p-value Districts Districts (1)-(2) (1)-(2) (Cameron) (1) (2) (3) (4) Output Capital Employees Plant Age *.11 Output per Worker Capital per Worker P-values in Col 1 are calculated from standard errors clustered at the district level. P-values in Col 2 are obtained using the bootstrap procedure developed by Cameron et al (2008). All monetary amounts are in 1000s of birr.

22 Figure: Difference in domestic plants productivity in treated vs control districts, relative to the year of a FDI plant opening (Research Design: Actual vs Planned). TFP Difference: Treatment - Control Districts Difference in TFP relative to year of opening Years since opening

23 Figure: Domestic plants productivity, relative to the year of a FDI plant opening (Research Design: Actual vs Planned). TFP Years since opening Treatment Districts Control Districts

24 Outline A Simple Model Data and Descriptive Stats Estimation and Main Evidence - RD 1: Actual vs Planned FDI - Survey Module Evidence Robustness, and Further Evidence

25 Table 7: FDI-related outcomes of domestic plants (% of domestic plants) (1) Directly adopted production processes by observing foreign plants in same industry 12.6 foreign plants did not try to prevent the observation/adoption 77.3 (% of plants answering YES to above question) (2) Benefited from employing Former FDI workers 7.2 (3) Technology transfer from FDI customers 4.5 (4) Technology transfer from FDI suppliers 1.79 (5) Use technology licensed from foreign plants 10.2 (6) Changed production technologies due to competition from FDI 15.3 At least one of the above outcomes (1) to (4) 17.8 At least one of the above outcomes (1) to (6) 24.6 Number of 1,398 observations Note: Author s compilation based on and FDI survey module 1

26 Directly adopted Table 8: Linkages and Change of Technology by Domestic Plants Labor link Customer link Supply link Any link (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Yes No p-value Yes No p-value Yes No p-value Yes No p-value of diff. of diff. of diff. of diff. 2 production processes by observing FDI plants in the same industry Use technology licensed from foreign plants Changed production technologies due to competition from FDI N 97 1, , , ,140 Labor linked plants are defined as those hiring a former FDI employee, supply-linked plants are defined as those selling output to FDI plants, and customer-linked plants are defined as those buying raw material from FDI plants. Columns compare plants reporting each type of linkage to those who do not.

27 Table 9: Reported Benefits from Domestic Firms Linkages to FDI Firms Benefit Share of observations Labor Linkages Production Technologies 0.65 Management and Organizational Practices 0.14 Knowledge of How to Export 0.09 Others 0.11 Customer Linkages Production Technologies 0.65 Management and Organizational Practices 0.17 Knowledge of How to Export 0.01 Others 0.16 Supply Linkages Product Design 0.40 Worker Training 0.19 Production Technologies 0.18 Logistics 0.11 Organization Structure 0.12 Any Linkage Production Technologies 0.45 Product Design 0.20 Management and Organizational Practices 0.13 Logistics Including Exporting 0.07 Worker Training 0.07 Others 0.08 Notes: The total number of firms included is equal to 179. Product design includes increases in the variety and quality of products. Worker training includes training of managers and those they supervise. Supply chain logistics includes better marketing and distrubution of products as well as supply chain management. Management and organizational practices include managerial practices, organizational structures and physical upkeep of premises. 3

28 Outline Data and Descriptive Stats RD 1: Exploiting assignment of land by Gov t Survey Module Evidence RD2: Actual vs Planned FDI Investments Robustness, and Further Evidence

29 What have we learned? We presented evidence on FDI effects, in particular on the way in which knowledge is transferred from FDI to domestic plants knowledge transfer through labor flows; also evidence for learning by observation, customer/supplier relationships foreign plants attract new economic activity Cannot completely rule out possibility that some of estimated effect reflects correlated unobservables But similar results with RD 1 & 2, and overall evidence supports hypothesis of positive FDI effect

30 Intro Simple Model Data Estimation and Main Evidence Inside the Black Box of TT Further Evidence Conclusions Extra Girum Abebe (EDRI, Ethiopia), Margaret McMillan (Tufts), Michel Sera nelli (Toronto) Foreign Direct Investment and Knowledge Di usion in Poor Locations: Evidence from Ethiopia