Deforestation in Decentralized and Democratic Indonesia

Transcription

1 Deforestation in Decentralized and Democratic Indonesia Vid Adrison Institute for Economic and Social Research Faculty of Economics University of Indonesia (LPEM FEUI) Presented at Forum Kajian Pembangunan (FKP) Roadshow Banda Aceh, Palembang and Banjarmasin March 11 th 13 th, 2014

2 Acknowledgment This independent research is made possible by/with the support of the American People through the United States Agency for International Development (USAID). The contents of this research are the sole responsibility of the author and do not necessarily reflect the views of USAID or the United States Government or LPEM FEUI. I thank all team members namely Isfandiarni, M Shauqie Azar, Cita Wigjoseptina, Dhaniel Ilyas, Farma Mangunsong, Yusuf Sofiyandi Simbolon, Bhaskara Adiwena and Widi Laras Sari for their excellent support during the research. I thank Benjamin Olken (Massachusetts Institute of Technology) for sharing the dataset used in Burgess et al (2011), Center of Climatic Research University of Delaware for the rainfall dataset and Rhita Simorangkir for sharing the data. I would also thank to external reviewers for the earlier version of this paper, namely Budy Resosudarmo (Australian National University), Leonid Polishchuk and Ritu Nayyar-Stone (Urban Institute) 2

3 Background Indonesia s total forest area has decreased from million sq km in 1990, to million sq km in 2011 (World Development Indicators, 2013) Contributing factors to deforestation Arnold (2008): regulatory conflict between forestry law and decentralization law Burgess et al (2011): increased number of jurisdiction and district local election Massive conversion from forest to plantation Law 33/2004 on Fiscal Balance Revenue sharing is a positive function of forestry extraction Given LOSR share remain low and forestry resources are relatively well distributed, does this provide sufficient incentive to extract forestry resources at higher level?

4 Policy Problems Reducing forestry-related emission carbon in Indonesia would have a (potential) significant impact globally Forestry utilization has both benefit and cost Increased economic activity (direct and indirect) Average District Local Own Source Revenue in Indonesia is very low (+/- 7% of total district revenue) Forestry resources are relatively well distributed compared to other natural resources Local government forestry revenue sharing is a positive function of forestry extraction Increased probability of natural disaster (flood and landslide) Related laws are on the amendment list (Decentralization, Fiscal Balance and Forestry)

5 Research Questions 1. Does forestry decentralization lead to increased deforestation? 2. Do natural disasters such as flood and landslide tend to occur more frequently in area with high rate of deforestation? 3. Do districts receiving forestry revenue sharing experience higher economic growth than it would be otherwise?

6 Methodology Literature Review Conduct in-depth interviews with relevant stakeholders in 4 districts with significant amount of forestry revenue sharing Create conceptual framework Empirically test using econometrics

7 Literature Review (1) Effect of Decentralization and Democratization on Deforestation: Indonesian context Legalizing illegal logging by imposing fees for timber (Cason and Obidzinki, 2002) Higher community s valuation leads to higher payoff (Engel and Palmer, 2006) Regulatory conflict contribute to higher deforestation (Arnold, 2008) Increased jurisdiction and local election lead to higher deforestation (Burgess et al, 2011)

8 Literature Review (2) Effect of Decentralization and Democratization on Deforestation: International and Cross Countries Context Decentralized political and fiscal power in Guatemala encourage the mayors to invest more on their staff and capital in the forestry sector compare relatively to a stringent Bolivia central government (Andersson and Gibson, 2006) Conflicting authorities in the forestry sector with almost identical responsibility result in an ineffective policy implementation in Philippines (Balooni et al, 2008) Countries with abundant resources but low democratic institution tend to corrupt (Bhattacharyya and Hodler, 2010) Decentralization leads to increase in forest investment in Uganda, Mexico and Bolivia, but decrease significantly in Kenya (Coleman and Fleischman, 2012)

9 In-Depth Interview Results 1. Under-utilized reforestation fund due to PP 35/ Local forestry offices feel they have insufficient resources to perform their assigned function as described in PP 38/ Mapping is a common problem 4. Deforestation usually takes place in a particular distance inside forest boundary. 5. Plantation also contributes to deforestation 6. Some mining activities take place even in the conservation area, where forestry utilization is strictly prohibited.

10 Conceptual Framework Graph 1: Impact of Forestry Revenue Sharing on Forestry Extraction C = 1 + γ ψ E + Λ E Φ E Output (Y), Y = φ Z + δ Ω E + wφ E Y = φ Z + δω E NB1 C = ψ E + Λ E Φ E NB2 NB0 Y = φ Z E2 E0 E1 Level of Extraction, (E)

11 Empirical Analysis Dependent Variables Deforestation: Burgess et al (2011) , all districts in Sumatera, Kalimantan, Sulawesi and Papua Disasters: National Agency for Disaster Management (BNPB) District GDP: Central Bureau of Statistics (BPS) Independent Variables Center for Climatic Research, University of Delaware Monthly average precipitation at village level, aggregated into district level Central Bureau of Statistics: Socio economic variables Ministry of Finance : District Government Budget General Election Commission: Political Party Concentration and Local Election year Regressions: Random Effect and Fixed Effect Deforestation and GRDP Fixed Effect Poisson Natural Disasters

12 Econometric Results 1. Forestry decentralization leads to higher deforestation rate. This result is consistent even for conservation and protection forest 2. There is statistical evidence that mining activities are responsible for deforestation in conservation forest. 3. No statistical evidence on effectiveness of district spending on environmental function to reduce deforestation rate. 4. Similar to Burgess et al (2011), we found statistical evidence that local district head election is related with deforestation However, our empirical model does not say who is responsible for deforestation before local district election.

13 Econometric Results (2) NATURAL DISASTERS 1. We find statistical evidence that flood, landslide and flood with landslide tend to occur more frequently in the district with higher forest degradation. This implies that deforestation decreases environmental supporting capacity of the forest. DISTRICT GRDP 1. We find that forestry revenue sharing increases local economic output, although the impact is economically small. One percent increase in forestry revenue sharing is associated with 0.003% to 0.006% increase in Non Oil and Gas GRDP 0.004% to 0.009% in term of Per Capita Non Oil and Gas GRDP.

14 Policy Recommendations Functional Assignment: Clear functional assignment on forestry resource management. Regulatory conflicts among laws must be addressed. If one among government objectives in forestry resource is to minimize the negative impact of forestry extraction, forestry resource management should be put as the function to be carried out by the central government. Revenue Sharing: Increasing the resources of local forestry authority by earmarking forestry revenue sharing. In-depth interview results indicate that local forestry offices do not have sufficient resources to perform their assigned function. Amend PP 35/2002 Allow the local government to spend reforestation fund on supporting activities for reforestation efforts.

15 Descriptive Statistics Obs Mean Std. Dev. Min Max DEPENDENT VARIABLES Deforestation Deforestation in Convertible Forest (Hectare) 2, , ,887.5 Deforestation in Conservation Forest (Hectare) 2, , ,775.0 Deforestation in Production Forest (Hectare) 2,456 1, , ,275.0 Deforestation in Protection Forest (Hectare) 2, ,012.5 Deforestation Other Forest 2, , ,087.5 Natural Disaster Number of Flood 2, Number of Landslide 2, Number of Flood with Landslide 2, INDEPENDENT VARIABLES Forest Size Convertible Forest (Hectare) 2,763 58, , ,512.5 Conservation Forest (Hectare) 2,763 57, , ,136,881.0 Production Forest (Hectare) 2, , , ,350,194.0 Protection Forest (Hectare) 2,763 98, , ,720,056.0 Other Forest (Hectare) 2,763 95, , ,137.5 Normalized Value of Convertible Forest (Current/Initial Stock) 1, Normalized Value of Conservation Forest (Current/Initial Stock) 1, Normalized Value of Production Forest (Current/Initial Stock) 2, Normalized Value of Protection Forest (Current/Initial Stock) 2, Normalized Value of Other Forest (Current/Initial Stock) 2, Local Economic Structure GRDP (Non Oil and Gas) 3,076 1,387,517 2,274,908-33,400,000 Per Capita GRDP (Non Oil and Gas) 2, Share of Agriculture in Non Oil and Gas GRDP 2, Share of Mining in Non Oil and Gas GRDP 2, Share of Manufacturing in Non Oil and Gas GRDP 2, Local Government Finance Share of Local Own Source Revenue (%) 1, Natural Log of Forestry Revenue Sharing 3, Share of Environmental Spending in Budget (%) 1, Share of Infrastructure Spending in Budget (%) 1, Local Politic Local Parliament Concentration (HHI Index) 2, Human Capital Mean Years of Schooling 1, Weather Maximum Precipitation 2, ,

16 Regression Results (Random Effect) 16

17 Regression Results (Fixed Effect) 17

18 Natural Disaster Regression Results FLOOD LANDSLIDE FLOOD WITH LANDSLIDE Share of Environmental Spending in Budget (2.17)** (1.21) (1.37) (1.51) (0.65) (0.60) (0.74) (0.53) (0.77) Deforestation in Convertible Forest (Lag 1) (1.22) (1.54) (0.54) (0.25) (1.69)* (1.52) Deforestation in Convertible Forest (Lag 2) (1.19) (1.72)* (1.41) (1.06) (0.25) (0.20) Deforestation in Conservation Forest (Lag 1) (0.13) (1.07) (0.18) (0.22) (0.06) (0.95) Deforestation in Conservation Forest (Lag 2) (0.99) (0.58) (0.60) (0.53) (0.98) (1.46) Deforestation in Production Forest (Lag 1) (0.89) (1.05) (0.48) (0.64) (1.37) (1.31) Deforestation in Production Forest (Lag 2) (0.19) (0.64) (0.96) (0.69) (1.02) (0.79) Deforestation in Protection Forest (Lag 1) (0.42) (0.37) (0.31) (0.18) (0.57) (0.10) Deforestation in Protection Forest (Lag 2) (2.07)** (2.37)** (0.84) (0.90) (0.07) (0.26) Deforestation Other Forest (Lag 1) (0.12) (1.04) (1.70)* (0.55) (0.98) (0.46) Deforestation in Other Forest (Lag 2) (1.59) (2.03)** (1.33) (1.07) (0.74) (0.10) Ratio of Current Total Forest to Initial Stock (5.41)*** (1.78)* (2.35)** (2.15)** (1.50) (1.65)* (3.25)*** (2.70)*** (2.65)*** Maximum Precipitation (2.10)** (4.11)*** (4.22)*** (0.26) (0.52) (0.44) (1.24) (2.39)** (2.14)** Observations Number of district id 2008, using 2008 ids, dejure Absolute value of z statistics in parentheses * significant at 10%; ** significant at 5%; *** significant at 1% 18

19 GRDP Regression Results NON OIL GRDP NON OIL PER CAPITA GRDP Random Effect Fixed Effect Random Effect Fixed Effect Without AR With AR Without AR With AR Without AR With AR Without AR With AR Share of Local Own Source Revenue (1.27) (0.38) (2.31)** (0.56) (2.20)** (0.53) (2.72)*** (0.50) Mean Years of Schooling (4.94)*** (4.14)*** (4.50)*** (16.35)*** (7.56)*** (4.62)*** (6.63)*** (7.48)*** Share of Agriculture Sector in GRDP (Non Oil and Gas) (9.33)*** (8.78)*** (8.28)*** (11.82)*** (6.37)*** (7.53)*** (4.16)*** (3.77)*** Share of Manufacturing Sector in GRDP (Non Oil and Gas) (7.02)*** (4.88)*** (6.76)*** (8.44)*** (5.12)*** (3.42)*** (5.45)*** (6.27)*** Natural Log of Forestry Revenue Sharing (8.81)*** (5.47)*** (9.41)*** (3.19)*** (10.73)*** (6.63)*** (10.57)*** (4.49)*** Share of Infrastructure Spending in Budget (8.08)*** (4.76)*** (8.35)*** (2.92)*** (5.84)*** (4.14)*** (5.19)*** (2.88)*** 1 Year Before Election (0.51) (0.60) (0.68) (0.02) (1.04) (0.91) (1.08) (0.89) 2 Years Before Election (0.32) (0.69) (0.35) (1.00) (1.04) (2.82)*** (1.05) (1.11) Constant (98.07)*** (132.53)*** (106.00)*** (173.86)*** (4.54)*** (10.72)*** (4.24)*** (29.23)*** Observations Number of district id 2008, using 2008 ids, dejure Absolute value of z statistics in parentheses * significant at 10%; ** significant at 5%; *** significant at 1% 19

20 Thank You 20