Is Divorce a Solution? Decentralization Effect on Economic Growth in Post-Civil Conflict Countries

Samer Hamati

doi:10.1515/peps-2018-0055

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Is Divorce a Solution? Decentralization Effect on Economic Growth in Post-Civil Conflict Countries

Samer Hamati

Veröffentlicht/Copyright: 27. Juni 2019

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Aus der Zeitschrift Peace Economics, Peace Science and Public Policy Band 25 Heft 3

Abstract

Civil conflict is the nation’s most important historical event, and it became more frequent in countries already emerged from previous conflicts. High economic growth, as well as other institutional procedures, is key to break this conflict trap. Thus, the current article explores the role decentralization may play to enhance economic growth in post-civil conflict countries. In order to avoid untrue peaceful cases, the article adopted a strict criterion of post-conflict periods, leading to a small dataset. Distinguishing between two forms of decentralization and using two equations with different techniques, the article finds a hampering effect of fiscal decentralization on economic growth in countries emerging from civil conflicts, while it finds insignificant mixed effects of political decentralization. These findings support the distinction made between the real de facto decentralization and the official de jure one. They validate the belief that although central authorities in many countries pretend to apply decentralization, they limit its effectiveness by some legal procedures creating “fake” decentralization.

Keywords: civil conflict; decentralization; economic growth; fixed effects; war recurrence

Appendix

Table 6:

The full and the short samples of political decentralization.

Country	Last year of conflict	First year of peace	Post-Conflict GDP pc growth (%)	Post-Conflict GDP pc growth-average (full peace period)	Serial number of this war in the country	Conflict years	Pre-war year	Wartime combined	Peacetime	Peace period (years)	Sustainable political decentralization	Three consecutive years of peace
Angola	1995	1996	8.03	3.98	1	21	1974	1975–1995	1996–1997	2
Angola	2002	2003	1.58	6.09	2	5	1997	1998–2002	2003–2014	12	1	1
Argentina	1977	1978	−5.90	1.31	1	4	1973	1974–1977	1978–2014	37		1
Azerbaijan	1994	1995	−12.81	0.30	1	3	1991	1992–1994	1995–1996	2
Azerbaijan	1998	1999	6.46	10.05	2	2	1996	1997–1998	1999–2005	7		1
Bangladesh	1991	1992	3.09	3.67	1	17	1974	1975–1991	1992–2014	23	1	1
Bolivia	1967	1968	−13.93	0.80	1	1	1966	1967	1968–2014	47		1
Bosnia	1995	1996	92.36	10.63	1	4	1991	1992–1995	1996–2014	19	1	1
Burundi	2006	2007	1.14	1.26	1	13	1993	1994–2006	2007	1
Burundi	2008	2009	−0.11	0.64	2	1	2007	2008	2009–2014	6		1
Cambodia	1975	1976		3.15	1	9	1966	1967–1975	1976–1977	2
Cambodia	1998	1999	9.22	6.28	2	21	1977	1978–1998	1999–2014	16		1
Cameroon	1961	1962	0.84	0.87	1	2	1960	1961	1962–1983	22		1
Chad	1972	1973	−10.55	−1.59	1	7	1965	1966–1972	1973–1975	3		1
Chad	1984	1985	18.50	2.09	2	9	1975	1976–1984	1985–1986	2
Chad	1987	1988	11.84	0.60	3	2	1985	1986–1987	1988	1
Chad	1994	1995	−2.07	1.76	4	6	1988	1989–1994	1995–1996	2
Chad	2003	2004	28.72	7.06	5	7	1996	1997–2003	2004–2005	2
Chad	2010	2011	−3.19	2.04	6	6	2004	2005–2010	2011–2014	4		1
Congo, Dem. Rep.	1965	1966	3.83	0.03	1	2	1963	1964–1965	1966	1
Congo, Dem. Rep.	1967	1968	1.38	−1.33	2	1	1966	1967	1968–1976	9		1
Congo, Dem. Rep.	1978	1979	−2.34	−4.82	3	2	1976	1977–1978	1979–1995	17		1
Congo, Dem. Rep.	2001	2002	−0.13	2.29	4	6	1995	1996–2001	2002–2005	4		1
Congo, Dem. Rep.	2008	2009	−0.42	3.55	5	3	2005	2006–2008	2009–2014	6		1
Congo, Rep.	1999	2000	4.90	2.84	1	3	1996	1997–1999	2000–2001	2
Congo, Rep.	2002	2003	−1.45	1.85	2	1	2001	2002	2003–2014	12		1
Croatia	1995	1996	10.00	2.58	1	1	1994	1995	1996–2014	19	1	1
Cuba	1960	1961		2.55	1	2	1956*	1957–1958	1959–2014	55
El Salvador	1991	1992	6.14	2.40	1	13	1978	1979–1991	1992–2014	23		1
Ethiopia	2013	2014	7.21	7.21	1	50	1963	1964–2013	2014	1
Georgia	1993	1994	−9.49	5.51	1	2	1991	1992–1993	1994–2014	21	1	1
Guatemala	1995	1996	0.48	1.25	1	30	1965	1966–1995	1996–2014	19		1
India	1960	1961	1.68	1.66	1	4	1955*	1956–1959	1960–1961	2
India	1971	1972	−2.82	3.47	2	10	1961	1962–1971	1972–1981	10		1
India	2010	2011	5.23	5.16	3	29	1981	1982–2010	2011–2014	4		1
Indonesia	1961	1962	−0.75	3.37	1	4	1960	1961	1962–1974	13		1
Indonesia	1988	1989	7.11	3.48	2	13	1975	1976–1988	1989–1996	8		1
Indonesia	2005	2006	4.12	4.35	3	9	1996	1997–2005	2006–2014	9	1	1
Iran	1968	1969	9.93	−0.13	1	2	1966	1967–1968	1969–1978	10		1
Iran	1988	1989	2.88	6.83	2	9	1979	1980–1988	1989	1
Iran	1990	1991	10.40	2.44	3	1	1989	1990	1991–1992	2
Iran	1997	1998	0.82	1.63	4	2	1995	1996–1997	1998	1
Iran	2001	2002	6.11	3.86	5	3	1998	1999–2001	2002–2004	3		1
Iran	2011	2012	−7.76	−3.59	6	7	2004	2005–2011	2012–2014	3		1
Iraq	1970	1971	1.90	4.57	1	9	1961	1962–1970	1971–1972	2
Iraq	1996	1997	17.50	5.30	2	24	1972	1973–1996	1997–2002	6		1
Israel	1996	1997	1.31	1.74	1	47	1949	1950–1996	1997–1999	3	1	1
Israel	2012	2013	1.34	1.08	2	13	1999	2000–2012	2013–2014	2
Laos	1961	1962			1	3	1958*	1959–1961	1962–1963	2
Laos	1973	1974		1.63	2	10	1963	1964–1973	1974–1988	15		1
Laos	1990	1991	1.35	4.88	3	2	1988	1989–1990	1991–2014	14		1
Lebanon	1960	1961			1	1	1957*	1958	1959–1974	16		1
Lebanon	1976	1977			2	2	1974	1975–1976	1977–1981	5		1
Lebanon	1986	1987		−8.66	3	5	1981	1982–1986	1987–1988	2
Lebanon	1990	1991	35.72	3.48	4	2	1988	1989–1990	1991–2014	14		1
Liberia	2003	2004	0.67	3.05	1	4	1998	1999–2002	2003–2014	12		1
Mauritania	1978	1979	1.83	0.63	1	3	1975	1976–1978	1979–2014	36		1
Morocco	1989	1990	0.88	2.51	1	15	1974	1975–1989	1990–2014	25		1
Mozambique	1992	1993	4.45	4.22	1	15	1977	1978–1992	1993–2014	22		1
Myanmar	2011	2012		7.35	1	63	1948*	1949–2011	2012	1
Myanmar	2013	2014	7.58	7.58	2	1	2012	2013	2014	1
Nepal	2006	2007	2.34	3.40	1	11	1995	1996–2006	2007–2014	8		1
Nicaragua	1979	1980	1.63	−3.15	1	3	1976	1977–1979	1980–1981	2
Nicaragua	1990	1991	−2.36	1.88	2	9	1981	1982–1990	1991–2014	14		1
Nigeria	1970	1971	11.61	1.29	1	4	1966	1967–1970	1971–2010	40		1
Pakistan	1971	1972	−1.90	1.16	1	1	1970	1971	1972–1974	3		1
Pakistan	1977	1978	4.73	2.37	2	3	1974	1975–1977	1978–2003	26		1
Pakistan	2004	2005	5.50	1.95	3	1	2003	2004	2005	1
Peru	1999	2000	1.29	4.03	1	18	1981	1982–1999	2000–2006	7		1
Peru	2010	2011	5.07	3.75	2	4	2006	2007–2010	2011–2014	4		1
Rwanda	1994	1995	37.13	8.93	1	5	1989	1990–1994	1995	1
Rwanda	2002	2003	−0.27	4.84	2	7	1995	1996–2002	2003–2008	6		1
Rwanda	2012	2013	2.22	3.35	3	4	2008	2009–2012	2013–2014	2
Senegal	1998	1999	3.81	2.12	1	2	1996	1997–198	1999	1
Senegal	2001	2002	−1.97	0.94	2	2	1999	2000–2001	2002	1
Senegal	2003	2004	3.04	1.04	3	1	2002	2003	2004–2010	7	1	1
Senegal	2011	2012	0.28	0.43	4	1	2010	2011	2012–2014	3		1
Serbia	1991	1992		0.25	1	1	1990	1991	1992–1997	6		1
Serbia	1999	2000	8.10	3.96	2	2	1997	1998–1999	2000–2014	15	1	1
Sierra Leone	2001	2002	20.50	6.05	1	11	1990	1991–2001	2002–2014	13		1
Somalia	1996	1997			1	11	1985	1986–1996	1997–2000	4		1
Somalia	2002	2003			2	2	2000	2001–2002	2003–2005	3		1
South Africa	1988	1989	0.13	0.64	1	23	1965	1966–1988	1989–2014	26
Vietnam	1964	1965		4.83	1	10	1954*	1955-1964	1965–2014	50		1
Sri Lanka	1971	1972	−1.73	3.16	1	1	1970	1971	1972–1983	12		1
Sri Lanka	2001	2002	3.28	3.92	2	18	1983	1984–2001	2002	1
Sri lanka	2003	2004	4.02	4.81	3	1	2002	2003	2004	1
Sri Lanka	2009	2010	6.95	7.25	4	5	2004	2005–2009	2010–2014	5		1
Sudan	1972	1973	−2.41	2.21	1	9	1963	1964–1972	1973–1982	10		1
Syria	1982	1983	−2.11	1.10	1	4	1978	1979–1982	1983–2010	18		1
Tajikistan	1998	1999	2.31	5.71	1	7	1991	1992–1998	1999–2009	11		1
Tajikistan	2011	2012	5.10	4.81	2	2	2009	2010–2011	2012–2014	3		1
Thailand	1982	1983	3.65	4.20	1	9	1973	1974–1982	1983–2002	20		1
Turkey	2013	2014	1.62	1.62	1	20	1993	1994–2013	2014	1
Uganda	1992	1993	4.90	3.97	1	14	1978	1979–1992	1993	1
Uganda	2011	2012	1.05	0.72	2	18	1993	1994–2011	2012	1
Yemen	1970	1971			1	9	1961	1962–1970	1971–1978	8		1
Yemen	1982	1983		1.08	2	4	1978	1979–1982	1983–1993	11		1
Yemen	1994	1995	1.29	0.28	3	1	1993	1994	1995–2008	14		1
Zimbabwe	1979	1980	10.37	−0.40	1	7	1972	1973–1979	1980–2014	35	1	1
Timor-Leste	1999	2000	16.66	4.68	2	3	1996	1997–1999	2000–2014	15	1	1
Eritrea	1992	1993	13.81	1.53	1	29	1963	1964–1992	1993–2014	12	1	1

Source: UCDP/PRIO dataset and World Development Indicators (2017).
Since pre-1960 data are not available in the WDI, we use data of 1960 as pre-war data when a cell is indicated with *. 1 in columns12 and 13 means the condition is met. pc stands for per capita. Table 12 describes the variables.

Table 7:

Descriptive Statistics of the stricter sample of political decentralization dataset (4 consecutive years of peace).

Political decentralization	Post-Conflict GDP pc growth (%)^a	War period (years)	Post-Conflict GDP pc level (USD)^c	Economic damage (%)	Peace period (years)	Ethnic fractionalization^b	Secondary school enrollment^b	Executive constraints^b	Voice and accountability^b
61 Cases of post-conflict periods with at least one arrangement of political decentralization
Mean	3.25	7.71	1233	13.38	15.39	0.53	44.71	3.79	−0.68
SD	2.73	7.59	1442	46.62	10.54	0.26	25.88	2.04	0.67
Min	−4.37	1	146.8	−66.35	4	0.0023	5.61	1	−1.98
Max	11.46	30	7264	250.9	50	0.91	99.22	7	0.4
50 Cases of post-conflict periods
Mean	3.07	7.8	1155	16.31	15.04	0.54	42.07	3.54	−0.84
SD	2.68	7.44	1272	48.7	11.09	0.27	24.71	2.1	0.67
Min	−4.366	1	146.8	−66.35	4	0.0023	5.61	1	−1.98
Max	11.46	30	5189	250.9	50	0.91	99.22	7	0.395
11 Cases of post-conflict periods with no forms of political decentralization
Mean	3.99	7.27	1530	−3.36	17	0.53	57.56	4.9	−0.26
SD	2.93	8.59	2013	29.42	7.79	0.21	29.59	1.5	0.46
Min	−0.4045	1	212	−65.28	7	0.045	18.41	3	−1.26
Max	10.63	29	7264	19.77	35	0.8	89.23	7	0.30

Sources: Author’s computations based on Table 6.
^ameans that the value mentioned is an average for the whole PC period; ^bmeans that the value mentioned is an average for the first two years in the PC period; ^cmeans that the value mentioned is for the first year in the PC period; ^dmeans that the value mentioned is an average for the last 3 years in the pre-conflict period; ^emeans that the value mentioned is for the last year in the pre-conflict period. The GDP per capita is measured with constant 2005 USD. pc stands for per capita. Table 12 describes the variables.

Table 8:

Economic growth averages during the conflict circle between the two groups of countries.

Sustainable	Pre conflict	Pre conflict	Pre conflict	Pre peace	Pre peace	Pre peace	Pre peace	Pre peace	Peace	Peace	Peace	Peace	Peace	Peace
PD	−3	−2	−1	−5	−4	−3	−2	−1	1	2	3	4	5	6
No	−1.5	2.9	3.4	2.01	1.99	1.01	1.12	2.65	3.07	3.67	3.32	3.02	2.44	2.94
With	1.5	1.6	1	0.5	0.1	−1.57	−6.8	0.21	13.97	10.14	4.7	4.46	4.48	3.67

Source: Author’s computations based on Table 6.
Pre conflict indicates the peaceful period before the conflict erupts. Pre peace indicates conflict years before the peace comes. Peace indicates the peaceful post-conflict period. PD stands for political decentralization. Table 12 describes the variables.

Table 9:

Robustness check for political decentralization equation.

Variables	Model PD5	Model PD6	Model PD7	Model PD8
Log of initial GDP pc		−0.00755**	−0.0762	−0.00631
		(0.00365)	(0.0768)	(0.00525)
Log of capital formation		0.0286	0.249	0.00843
		(0.0184)	(0.213)	(0.0171)
Log of public consumption		−0.00852	0.0980	−0.00187
		(0.00625)	(0.114)	(0.0121)
Population growth		−0.00828***	−0.0387	−0.00881
		(0.00253)	(0.0343)	(0.00725)
Executive constraints		−0.00142	0.0182	−1.23e-05
		(0.00183)	(0.0229)	(0.00187)
Secondary school enrollment		0.000320**	−6.88e-05	0.000373
		(0.000137)	(0.000567)	(0.000223)
Trade openness		0.000170	−0.00343	0.000397**
		(0.000102)	(0.00337)	(0.000165)
Political decentralization	0.00849	−0.00221	−0.0498	0.00242
	(0.00845)	(0.00430)	(0.0560)	(0.0135)
Economic damage		6.49e-05	−0.000600	0.000450**
		(9.02e-05)	(0.000583)	(0.000212)
Ethnic fractionalization		−0.0142	0.110	−0.0412*
		(0.0170)	(0.142)	(0.0236)
Obs.	57	32	12	20
R²	0.018	0.636	0.976	0.773
RMSE	0.025	0.017	0.011	0.015

Source: Authors’ computations based on regressing Equation (1).
The regressions in Models PD5 and PD6 build on an annual unbalanced panel covering 61 cases of post-civil conflict periods in 47 countries and spanning between 1960 and 2014. The regression in Model PD7 builds on a sub-group that includes only the PCCs where the conflict incompatibility concerns controlling over territory, while the regression in Model PD8 builds on a sub-group that includes only the PCCs where the incompatibility concerns controlling over central power. Robust standard errors in parentheses. ***, **, *indicate significance at the 1, 5, and 10%, respectively. pc stands for per capita. Table 12 describes the variables.

Table 10:

Robustness check of fiscal decentralization equation.

Variables	Model FD6	Model FD7	Model FD8	Model FD9	Model FD10
Log of capital formation		0.0576**	0.0608***	0.0310***	0.229***
		(0.0246)	(0.0147)	(0.00853)	(0.0207)
Log of public consumption		−0.0458***	−0.0261	−0.0488***	0.0169
		(0.00879)	(0.0259)	(0.00925)	(0.0708)
Population growth		−1.756***	−2.779***	−1.540***	−4.178
		(0.401)	(0.853)	(0.345)	(3.376)
D. Executive constraints		0.00464	0.00406	0.0222	0.000862
		(0.00401)	(0.00723)	(0.0164)	(0.00433)
D. Secondary school enrollment		0.00142	0.000912	0.00336	−0.000807
		(0.00242)	(0.00157)	(0.00402)	(0.00212)
Trade openness		−0.000472	−0.000703**	5.73e-05	−0.000773
		(0.000622)	(0.000343)	(0.000441)	(0.00108)
Fiscal decentralization	−0.0150	−0.0351**	−0.0485**	−0.0279**	−0.137**
	(0.0142)	(0.0162)	(0.0218)	(0.0108)	(0.0451)
Ethnic fractionalization			0.0801
			(0.0810)
Economic damage			−3.16e-05
			(0.000531)
Observations	162	116	101	80	36
R²	0.011	0.291		0.276	0.781
Number of wars	17	16	14	9	7
F-test for joint significant of fixed effects	14.27***	36.41***		5678.62***	37.03***
RMSE	0.033	0.03		0.031	0.021
Sigma_u			0.035
Sigma_ε			0.029
Rho			0.59
Wald χ²			1.867

Source: Authors’ computations based on regressing Equation (4).
The regressions in Models FD6, FD7, and FD8 build on an annual unbalanced panel covering 61 cases of post-civil conflict periods in 47 countries and spanning between 1960 and 2014. The regression in Model FD9 builds on a sub-group that includes only the PCCs where the conflict incompatibility concerns controlling over territory, while the regression in Model FD10 builds on a sub-group that includes only the PCCs where the incompatibility concerns controlling over central power. Robust standard errors in parentheses. ***, **, *indicate significance at the 1, 5, and 10%, respectively. We estimate Model FD8 using Hausman-Taylor estimator, with expenditure decentralization, economic damage, population growth, and executive constraints are treated as endogenous variables. D. means that we use the first differences for this variable. Description of the variables used is in Table 12.

Table 11:

Between and within components of the standard deviation of our data.

Variables		Mean	SD
Log of economic growth pc	Overall	0.025	0.055
	Between		0.026
	Within		0.049
Log of economic level pc	Overall	6.9	0.99
	Between		1.033
	Within		0.206
Log of capital formation	Overall	2.985	0.426
	Between		0.332
	Within		0.305
Log of public consumption	Overall	2.540	0.537
	Between		0.469
	Within		0.264
Log of population growth	Overall	0.0198	0.011
	Between		0.011
	Within		0.006
Executive constraints	Overall	0.015	0.557
	Between		0.146
	Within		0.549
Trade openness	Overall	66.285	32.779
	Between		29.689
	Within		17.307
Economic damage	Overall	6.445	32.444
	Between		44.159
	Within		0
Secondary school enrollment	Overall	1.293	2.270
	Between		1.234
	Within		2.126
Expenditure decentralization	Overall	0.445	0.398
	Between		0.358
	Within		0.227
Ethnic fractionalization	Overall	0.524	0.247
	Between		0.252
	Within		2.23E-16

Source: Authors’ computations.
SD stands for standard deviations. The analysis builds on an annual unbalanced panel covering 61 cases of post-civil conflict periods in 47 countries and spanning between 1960 and 2014. Overall stands for the overall deviation; Between stands for the deviation between countries; Within stands for the overtime deviation within countries. pc stands for per capita. Table 12 describes the variables.

Table 12:

Definitions and sources of the variables used.

Variables	Description	Unit	Source/Based on
Per capita GDP Growth in Political Decentralization Equation	The difference in the log of per capita GDP between the end of the conflict and the end of the PC period	% Annual	World Bank/WDI
Per capita GDP Growth in Fiscal Decentralization Equation	The difference in the log of per capita GDP in two consecutive years	% Annual	World Bank/WDI
Log of initial GDP pc	The logarithmic value of per capita GDP in the first peaceful year	constant 2005 USD	World Bank/WDI
Political decentralization	A dummy variable taking a unitary value if the peace agreement involves at least one form of decentralization	0/1	Uppsala Conflict Data Program/Peace Agreement Dataset
Sustainable political decentralization	A dummy variable taking a unitary value if the peace agreement involves at least one form of decentralization and the agreement sustains	0/1	Uppsala Conflict Data Program/Peace Agreement Dataset
Log of capital formation	The logarithmic Value of the gross fixed capital formation as a percentage of GDP	% of GDP	World Bank/WDI
Log of public consumption	The logarithmic Value of the governmental current expenditure as a percentage of GDP	% of GDP	World Bank/WDI
Population growth in political decentralization equation	The difference in the log of the population between the end of the conflict and the end of the PC period	% Annual	World Bank/WDI
Population growth in fiscal decentralization equation	The difference in the log of the population in two consecutive years	% Annual	World Bank/WDI
Executive constraints	The extent of institutionalized constraints on the decision-making powers of chief executives, whether individuals or collectivises. Values are expressed in a 7-category scale, ranging from unlimited authority to executive parity or subordination	1–7	Polity IV dataset
Secondary school enrollment	The ratio of total secondary enrollment, regardless of age, to the population of the age group that officially corresponds to that level of education	%	World Bank/WDI
Trade openness	The ratio of exports and imports (in the local currency) to GDP (in the local currency)	%	World Bank/WDI
Ethnic fractionalization	Ethnic fractionalization is measured by the ethnolinguistic fractionalization index. It measures the probability that two randomly drawn individuals from a given country do not belong to the same group. It ranges between 0 and 1. We use the religious fractionalization index when the ethnic index is absent	0–1	Alesina, Devleeschauwer, Easterly, Kurlat, and Wacziarg (2003)
Economic damage	The simple GDP change between the beginning and the end of a conflict	% of the pre-conflict GDP	World Bank/WDI
Expenditure decentralization index	It represents the average share of the local expenditures as a percentage of the overall expenditures in a specific country	%	World Bank/WDI

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Published Online: 2019-06-27

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Artikel in diesem Heft

https://doi.org/10.1515/peps-2018-0055

Schlagwörter für diesen Artikel

civil conflict; decentralization; economic growth; fixed effects; war recurrence