What Determines Firms Decision to Formalize?

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1 What Determines Firms Decision to Formalize? Empirical Evidence from Rural Indonesia Neil McCulloch Günther G. Schulze Janina Voss IDS, Univ. of Sussex/ UK Univ. of Freiburg/ Germany Fourth IZA/ World Bank Conference on Employment and Development Bonn, May 5, 2009

2 Motivation Informal sector is large most firms, much employment, particularly of the poor We don t know much about the pattern of formalization (who is formal and who isn t) We don t know much about the determinants of formalization (costs and benefits and how they vary by firm and owner characteristics) Formalization in Rural Indonesia 2

3 Structure of the Talk 1. Introduction 2. Our Data: The Rural Investment Climate Survey in Indonesia 3. The Empirical Approach 4. Costs and Benefits of Formalization 5. Who Goes Formal? 6. Concluding Remarks Formalization in Rural Indonesia 3

4 The Rural Investment Climate Survey (RICS) Survey in the field early 2006, data refer to 2005 Household, enterprise, community questionaires 2461 micro and small firms micro (1 4 empl., 2198 firms), small (5 19 empl.) Six districts throughout rural Indonesia, 149 villages Enterprises: 1757 household, 618 standalone, 146 listed Sector: 54 % trading, 35 % services, 11% manufacturing Manager/Owner: 63% male, 37 % female Formalization in Rural Indonesia 4

5 Business Licensing in Indonesia Complicated, unclear process, mainly at district level Required licenses: Tax identification number (NPWP) Physical licenses: Construction/building license (IMB) Sectoral licenses: trade license (SIUP), industrial registration (TDI) Business registration (TDP) Only 2 % of firms are fully licensed, 23% have at least one license Formalization in Rural Indonesia 5

6 Cost Benefit Approach Firms decide to get licensed if benefits > costs Avg. Costs: 550,000 IDR, 11 days per lic. Benefits: Taxes, bribes, sales, access to credit, government contracts? Do benefits depend on firm characteristics? Stylized facts: Licensed firms are larger and older, they pay more taxes, bribes, have better access to credit and sell more to the govnmt. Endogeneity problem! Formalization in Rural Indonesia 6

7 Econometric Approach Endogeneity problem e.g., do firms pay higher taxes due to the license or do high tax payers decide to get a license to reduce the tax burden? IV approach, instrument: community averages for licensing Interaction with firm characteristics to capture firm heterogeneity Formalization in Rural Indonesia 7

8 1. Taxes (1) OLS (2) 2SLS (3) 2SLS licensed (0.381)*** (0.581)** (1.116)*** L*qsales_ (0.944) L*qsales_ (1.184)* L*qsales_ (0.995)*** L*qsales_ (1.445)** education (0.060)*** (0.096)*** (0.089)*** age (0.011) (0.012)* (0.011)** female (0.228)* (0.213)* (0.193)** Ind_ethn (0.270) (0.251) (0.257)* chinese (0.636) (0.880) (0.910) islam (0.317) (0.345)* (0.334)** employee (0.036)*** (0.045)** (0.044)* lnsales (0.083)*** (0.059)*** lnfasset (0.037)** (0.031)*** (0.028)*** Firm age (0.015) (0.015) (0.014) villtax (0.062)*** (0.061)*** Constant (1.196)** (1.467)*** (1.357) Observations R-squared Robust standard errors in parentheses Regression contains district dummies * significant at 10%; ** significant at 5%; *** significant at 1% Add. Controls for Sectors, Rural/Urban, Owner residing in village, district dummies 8

9 1. Taxes Licensed firms pay less taxes! This effect is smaller for larger firms. It is stronger for rural firms (not shown). Evidence for discrimination (religion, ethnicity). Controls: Large firms pay more. Village effects Formalization in Rural Indonesia 9

10 2. Informal payments (1) (2) (3) (4) (5) (6) No instruments License instrumented amount Did pay amount Did pay amount Did pay licensed (0.307) (0.155) (0.958)** (0.464)*** (2.697)*** (1.445) L*lnsales (0.234)*** (0.123) Resides in vill (0.308)* (0.160) (0.447)*** (0.208)*** (0.415)*** (0.211)*** indethn (0.338) (0.139) (0.308) (0.170) (0.282) (0.171) chinese (0.621) (0.411) (0.705)* (0.529) (0.565)** (0.500) lnsales (0.089) (0.043)*** (0.095)* (0.043)*** (0.118)*** (0.060)* lnfasset (0.034) (0.017) (0.033)** (0.017) (0.031)*** (0.017) villcorrpt (0.227) (0.070)*** (0.212) (0.070)*** employee (0.028)** (0.033)** (0.036)** Constant (1.390)** (0.722)** (1.492) (0.783) (1.463) (0.801)** License Neighborhood effect discrimination Size effect Village effect Obs Robust standard errors in parentheses Additional controls for sector, rural/urban, age of firm, female, islam, education, age, district dummies

11 2. Informal Payments Licensing reduces probability of paying bribes! It reduces amount of bribes as well! Esp. Large firms profit from reduction in corruption payments Controls: Owner residing in the village pays less bribes Larger firms pay more and are more likely to Chinese pay more, village effects Formalization in Rural Indonesia 11

12 3. Total Revenue Additional controls: sectors, rural/urban, female, Chinese, Islam, residing in village, district dummies (1) (2) (3) OLS 2SLS Licensed (0.233)* (0.291) (0.349)*** L*qemployee_ (0.594) L*qemployee_ (0.502) L*qemployee_ (0.465)*** edu (0.030)*** (0.028)*** (0.027)*** age (0.003)** (0.005) (0.005) indethn (0.164)* (0.152) (0.161) qemployee_ (0.178) (0.148) (0.128) qemployee_ (0.176)** (0.158)*** (0.194)** qemployee_ (0.204)*** (0.207)*** (0.287)*** qlnfasset_ (0.176) (0.156) (0.155) qlnfasset_ (0.150)* (0.137) (0.135) qlnfasset_ (0.148) (0.153) (0.160) qlnfasset_ (0.139) (0.130) (0.130) entagedum_ (0.107)*** (0.107)*** (0.107)*** entagedum_ (0.141)*** (0.172)*** (0.166)*** villsales (0.095)*** (0.091)*** Constant (0.441)*** (1.180) (1.111) Observations R-squared Robust standard errors in parentheses Regression contains district dummies Education matters! Firm size Firm age * significant at 10%; Formalization ** significant at 5%; in *** Rural significant Indonesia at 1% 12

13 3. Business Expansion/ Revenue Again: Endogeneity Overall: No effect of formalization on revenue Large firms will gain from formalization, small ones will not. Controls: Factor input (labor matters) Education Firm age Formalization in Rural Indonesia 13

14 4. Further results 1. Access to credit largely unaffected by licenses 2. Access to government contracts: large firms will profit from licensing, no overall effect Formalization in Rural Indonesia 14

15 Determinants of Formality Previous results show which characteristics are associated with lower costs increased benefits. Reduced form Probit of Formality Sales, employment, assets, Sector, rural/urban Female, ethnicity, religion, Chinese Formalization in Rural Indonesia 15

16 Who goes formal? Results More likely: Large firms do (highest quintile in employmt, assets, sales) Chinese (by a third) Better educated owners Less likely Majority ethnicity (by 10%) Owners who live in the village (by 15%) Rural firms (by 15 20%) Cost differences (time, money) do not matter Formalization in Rural Indonesia 16

17 Concluding Remarks The main reason firms go formal is to reduce rent extraction! Firms that are easier targets (large, Chinese, minority ethnicity, out of village) have a bigger incentive to get a license Formalization in Rural Indonesia 17

18 Firms Decision to Formalize Probit: Marginal effects from probit regression on licensed (1) (2) Formalized? qlnsales_ (0.052) (0.045) qlnsales_ (0.051) (0.047) qlnsales_ (0.067)* (0.063) qlnsales_ (0.079)*** (0.074)** qemployee_ (0.044) (0.043) qemployee_ (0.054) (0.051) qemployee_ (0.072)** (0.063) qlnfasset_ (0.068) (0.069)* qlnfasset_ (0.058) (0.061) qlnfasset_ (0.070)** (0.068)** qlnfasset_ (0.069)*** (0.067)*** female (0.036) (0.036) indethn (0.041)** (0.042)** islam (0.084) (0.077) Chinese (0.158)** (0.156)** rural (0.031)*** (0.032)*** meancost (0.000) (0.000) meantime (0.002) (0.002) edu edu (0.010)*** (0.010)*** Residing in vill (0.064)** (0.064)** District dummies yes yes Observations Robust standard errors in parentheses Regression contains district dummies * significant at 10%; ** significant at 5%; *** significant at 1% Additional controls for sector and district dummies (0.010)*** Formalization in Rural Indonesia 18

19 ADDITIONAL MATERIAL Formalization in Rural Indonesia 19

20 Literature Levenson and Maloney (1998) older and larger firms invest in formality as they have proven to be successful Jäckle and Lee (2003) older and larger firms, Peru Fajnzylnber et al. (2006) quasiexperimental regres. Discont., Brazil, formalized firms have higher revenue, employm., investment McKenzie and Sakho (2006) Bolivia, IV approach formalization increases profits for small firms (2 5 wrks), micor and large firms lose Formalization in Rural Indonesia 20

21 RICS Geographical coverage Labuhan Batu, North Sumatra a plantation area Kutai, East Kalimantan an area rich in mineral resources Barru, South Sulawesi a forest fringe area Malang, East Java a rich agricultural area Badung, Bali a semi urban agglomeration area Sumbawa, NTB a dryland area Formalization in Rural Indonesia 21

22 Mean Size and Enterprise Age formal informal mean number of employees mean of log total sales mean enterprise age Formalization in Rural Indonesia 22

23 IV Approach: first stage Sargan test on overidentification passed Strong identification, high F statistic Community characteristics no strong instruments Village w/ high share of licensed firms may perform better, thus have higher benefits. Additional control for village averages for the respective benefit analyzed Formalization in Rural Indonesia 23

24 (1) (2) (4) (5) (6) First Stage IV Estimates Marginal effects from Probit regression on licensed Vill avg licensed (0.086)*** (0.086)*** (0.081)*** (0.084)*** (0.094)*** education (0.007)*** (0.007)*** (0.007)*** (0.007)*** (0.008)*** age (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** female (0.024) (0.024) (0.023) (0.024) (0.024) Resides in vill (0.076)*** (0.077)*** (0.074)*** (0.074)*** (0.074)*** indethn (0.058) (0.056) (0.054) (0.055) (0.053) Chinese (0.105) (0.105) (0.100) (0.100) (0.101) Islam (0.046) (0.047) (0.046) (0.047) (0.049) Empl above median (0.046)* (0.046)* (0.041)*** (0.046)* (0.044)* Sales above median (0.032) (0.033) (0.033) (0.033) Fixed assets a.med (0.018)*** (0.018)*** (0.016)*** (0.017)*** (0.018)*** Firm age above med (0.029) (0.029) (0.028) (0.028) (0.028) rural (0.029) (0.028) (0.027) (0.026) (0.027) manufac (0.028) (0.028) (0.028) (0.029) (0.028) service (0.019) (0.019) (0.019)* (0.018) (0.018) bank villtax Formalization in Rural Indonesia (0.007) villcorrpt (0.012) villsales (0.018) villgovs (0.004)** villcred Observations Robust standard errors in parentheses Regression contains district dummies * significant at 10%; ** significant at 5%; *** significant at 1% (0.024) (0.056)* 24

25 (1) (2) (3) (4) (5) (6) No instruments License instrumented amount Did pay amount Did pay amount Did pay 2. Informal payments licensed (0.307) (0.155) (0.958)** (0.464)*** (2.697)*** (1.445) L*lnsales (0.234)*** (0.123) edu (0.083) (0.042)** (0.091) (0.055) (0.087)* (0.055) age (0.012) (0.006)** (0.013) (0.007) (0.013) (0.007) female (0.307) (0.147) (0.307) (0.150) (0.277) (0.150) Resides in vill (0.308)* (0.160) (0.447)*** (0.208)*** (0.415)*** (0.211)*** indethn (0.338) (0.139) (0.308) (0.170) (0.282) (0.171) chinese (0.621) (0.411) (0.705)* (0.529) (0.565)** (0.500) islam (0.397) (0.286) (0.402) (0.319) (0.372) (0.313) lnsales (0.089) (0.043)*** (0.095)* (0.043)*** (0.118)*** (0.060)* lnfasset (0.034) (0.017) (0.033)** (0.017) (0.031)*** (0.017) villcorrpt (0.227) (0.070)*** (0.212) (0.070)*** Formalization in Rural Indonesia employee

26 Who goes formal? 1. Licenses affect firms differently The costs and benefits of formality Interacting characteristic cost or benefit sales taxes (+) other levies : outcome stage ( ) sales to government (+) fixed assets other levies : outcome stage ( ) sales to government (+) employees credit ( ) revenue (+) female taxes (+) other levies : selection stage (+) rural taxes ( ) other levies : selection stage ( ) outcome stage (+) manufacturing sector credit ( ) sales to government (+) Ind_ethnicity other levies : selection stage ( ) Chinese sales to government ( ) Islam revenue ( ) other levies: outcome stage (+) Formalization in Rural Indonesia 26

What Determines Firms Decisions to Formalize?

What Determines Firms Decisions to Formalize? Empirical Evidence from Rural Indonesia Neil McCulloch, Günther G. Schulze and Janina Voss Preliminary version, 16. February 2009 Abstract In this paper we