Fiscal Decentralization, Policy Hold-up,

and Rural Labor Mobility:An analysis of Chinese rural

governments’ incentives to promote “inter-provincial Undocumented labor

mobility”

Yiu Por (Vincent) CHEN DePaul university

For WISE, Xiamen University 2006

Outline of the presentation:

• Establishing the relationship between fiscal decentralization and undocumented labor mobility

• Measuring of variables• Estimation of a gravity model:

1. Fiscal needs at different level of government => inward looking behavior

2. Rural economic development => undocumented labor migration

Focus of the paper: Political Economy of Labor Mobility

• What is the impact of fiscal decentralization on factor mobility? Qian versus Young.

• Under What condition(s), fiscal decentralization may foster market development?

What is Fiscal Decentralization?

• Delegation of taxation rights and governance in the upper levels of government.

• Usually reduced to simple principal-to-agent type central-to-provincial analysis. (Oates, 1972; Qian and Weingast, 1996; Qian and Roland, 1998; Ma, 1999; Lin and Liu, 2000; Young, 2001)

What is “Policy hold-up”?

• A rent-seeking behavior from local level government that distort the implementation of certain policy from the central government for their own interest.

The conditions of “policy hold-up”

• Local economic development: Townships and Villages Enterprises development.

• Fiscal needs: local governments’ number=> operation cost of local government.

Market development and factor mobility under macro-institutional rigidity:

– Hukou system=>labor immobile.– Local capital was not mobile.

A Review of the Policy History in China in early 80’s The central government policy change: Township & village Enterprises (TVEs) Fiscal Decentralization Undocumented labor migration Objectives: -Restrain labor mobility to urban area -Reduce budget burden. -induced Pareto improving through rural industrialization. -Promote local economic development. Market development. Time line:

t = 1980 t=1982 (rural level), t=1985 (provincial level) t=1988 on

Response of rural level governments:

-Specific Investment (TVEs) -Increase local revenue & Fiscal Need. -More “Fees” extracted from at rural government level. => Policy Hold-up Created!! migrant work on both labor

sending and labor receiving areas.

Consequences:

Uneven development Hecksher-Ohlin type inter-provincial labor migration Rent extraction from labor

Village immigration to different types of destination (1982-87)

year 1986-7 1985-6 1984-5 1983-4 1982-3 Total Column %

Inter-povincial ImmigrationHukou Village ImmigrantTo urban 60.00 56.00 59.00 54.00 51.00 280.00 40.23row % 21.43 20.00 21.07 19.29 18.21To town 10.00 20.00 37.00 21.00 19.00 107.00 15.37row % 9.35 18.69 34.58 19.63 17.76To village 46.00 86.00 69.00 57.00 51.00 309.00 44.40row % 14.89 27.83 22.33 18.45 16.50Total 116.00 162.00 165.00 132.00 121.00 696.00% 16.67 23.28 23.71 18.97 17.39Non-hukou Village ImmigrantTo urban 116.00 88.00 71.00 35.00 19.00 329.00 44.46row % 35.26 26.75 21.58 10.64 5.78To town 27.00 51.00 22.00 18.00 10.00 128.00 17.30row % 21.09 39.84 17.19 14.06 7.81To village 92.00 91.00 52.00 28.00 20.00 283.00 38.24row % 32.51 32.16 18.37 9.89 7.07Total 235.00 230.00 145.00 81.00 49.00 740.00% 31.76 31.08 19.59 10.95 6.62

Source: 5% random sample of 1% 1987 Chinese Population Census

Hypotheses:

Fiscal Decentralization create “policy Hold-up”

-From Central Planning to Fiscal Decentralization => local economic development.

-Fiscal Need => self-interest behavior. E.g opt out outsider at receiving area (young, 2001).– Fiscal incentives of rural governments to

promote labor mobility/blockage are strongest at the lowest (village) level and weakens as the level moves up.

Data:

• 5 % random sample of 1 % 1987 China population census.

• China statistics from various years: complied by the China Center for Economics Research (CCER).

• China City Yearbooks

Measuring Variables

Measuring Local Economic Development and Fiscal Needs at the rural levels governments:

Local Economic Development:• Township and Village Enterprises’ Output

Fiscal Needs at rural levels:• number of villages per Town in a province.• number of Township governments per province.• E.g. opening a branch office vs. opening a new

company.

Source : C ited from W ong e t a l (1995: 82-3)N ote :"Sub-provincia l government" = G overnm ents below level 2.(level 2) Inc ludes 27 provinces and 3 m unic ipalities including B eijing, Shanghai and T ianjin.(level 3) with 151 prefectures and 185 prefec tura l leve l c ities. som e prefec tures has been e lim inated, and rural countiesare direc tly under c ity adm inistra tion.For exam ple , G uangdong, Hainan, J iangsu, and Liaoning Provinces.(level 4) with 1903 counites and 279 county-level c ities.(level 5) w ith 56000 tow nships and tow ns, and c ity distric ts.

C ity D istric ts(Level 4)

T ow ns(Level 5)

T ow nships(Level 5)

U rban C ounties(Level 4)

U R B A NC ities

(Level 3)

T ow ns(Level 5)

T ow nships(Level 5)

C ounty Level C ities(Level 4)

T ow ns(Level 5)

T ow nships(Level 5)

N onurban C ounties(Level 4)

R U R A LPrefec tures

(Level 3)

Province(Level 2)

C entra l G overnm ent(Level 1)

Figure 2: Number of Town Government and Village Committee (1978-1987)

650,000

700,000

750,000

800,000

850,000

900,000

950,000

1,000,000

1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988

Years

Num

ber

of C

omm

ittee

50,000

55,000

60,000

65,000

70,000

75,000

80,000

85,000

90,000

95,000

Committee

Towns

Measuring provincial level government incentives:

• Marginal Retention Rate (MRR)• From 23.5% to 100%

• Sharing Scheme• a = remitting a share of the local revenues; • b = remitting a share of local revenue in the case year and the• total remittance increases at a predetermined rate in the subsequent

years; • c = remitting a fixed amount of the revenues to the central government;

• d = remitting a fixed amount in the base year and the total• remittance increases at a predetermined rate in subsequent years;• e =receiving a fixed amount of subsidy from the central government; and

• f = receiving a fixed amount of subsidy in the base year and the total • subsidy increases at a predetermined rate in subsequent years;

• Political Decentralization index • 1-4, the higher number means the closer to the central govt. (Huang)

Table 5: Description for Provincial Level Fiscal Decentrailzation Index and other Interest Variables at 1985

Province MRR (%) MRR Group Sharing Scheme villtown TVE output (0,000) TVE per capita Party index

Shanghai 23.54 1 a 13.85 1667982.0 3788.11 3Tianjin 39.45 1 a 17.93 591399.3 1646.85 4Jiangsu 40.00 1 a 18.78 871527.9 167.61 1Beijing 49.55 1 a 11.64 767966.6 1944.22 3Liaoning 51.08 1 a 12.93 940167.3 430.54 1Zhejiang 55.00 1 a 13.35 466246.8 137.32 1Shandong 59.00 2 a 33.24 380339.2 56.98 2Hebei 69.00 2 a 13.73 287805.4 60.07 3Henan 80.00 2 a 22.27 191027.9 27.50 2Anhui 80.10 2 a 9.24 139752.3 31.53 1Hunan 88.00 2 a 14.18 158274.1 32.80 1Shanxi 97.50 3 a 16.82 196654.0 92.04 2Guizhou 100.00 3 f 6.65 25728.1 9.86 4Guangdong 100.00 3 c 6.71 515842.2 115.72 1Hubei 100.00 3 a 6.89 305993.4 78.03 1Yunnan 100.00 3 f 7.73 35456.2 11.73 1Ningxia 100.00 3 f 8.58 15277.3 46.16 1Qinghai 100.00 3 f 8.68 11606.2 39.85 1Sichuan 100.00 3 a 8.86 245746.4 28.23 1Innter Mongolia 100.00 3 f 8.89 66605.3 46.22 2Xinjiang 100.00 3 f 9.82 52089.6 56.50 2Jilin 100.00 3 e 11.04 224517.7 153.67 1Jiangxi 100.00 3 e 11.50 91537.8 31.73 1Gansu 100.00 3 e 11.56 29321.6 16.85 1Guangxi 100.00 3 f 11.58 40413.0 11.88 1Shaanxi 100.00 3 e 12.48 109250.2 44.37 1Heilongjiang 100.00 3 c 12.53 296355.5 147.96 1Fujian 100.00 3 e 16.12 138558.5 61.15 3

SOURCES. --- Sharing scheme, 1985-87 = Dangdai Zhongguo Caizheng Huiban Weiyuanhui, Dangdai Zhongguo Caizheng (Public finance in modern China) ( Beijing: China Social Science, 1988), pp. 376- 77; Provincial level Fiscal Index: MRR and Sharing Scheme are extraced and cited from Lin and Liu (2000)Note: 1. All variables are measure as of 1985. Villtown is in #, TVEs ouput (10 thousand, current price)., TVE per capita in yuan2. Please see the data description table attached for all other variables description3. Sharing schemes: a = remitting a share of the local revenues; b = remitting a share of local revenue in the case year and thetotal remittance increases at a predetermined rate in the subsequent years; c = remitting a fixed amount of the revenues to the central government; d = remitting a fixed amount in the base year and the totalremittance increases at a predetermined rate in subsequent years;e =receiving a fixed amount of subsidy from the central government; and f = receiving a fixed amount of subsidy in the base year and the total subsidy increases at a predetermined rate in subsequent years;

Figure 3: Inter-provincial Non-hukou Village-Rural Immigration by MRR Group (1982-7)

0

1

2

3

4

5

6

7

8

9

1982 1983 1984 1985 1986

YearSource: 5 % of 1 % Random Sample of 1987 Chinese Population Census

Note: The Provincial Grouping is according to the Rank of M arginal Retention Rate (M RR):Group 1: M RR<=55%, Group 2: M RR>55 & <=90%, Group 3: M RR>90%. Rural = Village + Town

Ave

rage

Num

ber

by G

roup

Group1

Group2

Group3

Method:

• A Gravity Model: captures the reduced form supply and demand of undocumented rural-rural migration.

• Mijt = Di (t-1) (local economic development +

number of rural govt. + institutional variables + other control variables)

+ Sj (t-1) (local economic development + number of

rural govt. + institutional variables + other control variables)

Dependent variable:

• Mij = ln(Inter-provincial illegal rural-rural labor migrant)

• Construction of pseudo-panel data:

28 X 28 matrix of 5 years (from 1982 to 1987)

Of undocumented labor flow

Other Lagged Independent Variables

• Output of township and village enterprises’

• Household Responsibility System (% of production Team turn to Household farming)

• Moving Cost: ln(road density per sq km)

• other control variables: gdp per capita, foreign direct investment per capita, log( agricultural output), log (agricultural population).

T ab le 3 : V ariab les D escrip tion T ab le (1982-1987 , p rov in cia l level)

V a ria b le s D e sc rip tio nlo g (in te r-p ro v in c ia l ru ra l-ru ra l n o n -h u k o u m ig ra n t)lo g o f N u m b e r o f in te r-p ro v in c ia l R u ra l-R u ra l m ig ra tio n = M ijlo g (T V E o u tp u t) T o w n sh ip & v illa g e c o lle c tiv e o u tp u t (1 0 th o u sa n d c u rre n t p r ic e )v illa g e p e r T o w n A v e ra g e n u m b e r o f v illa g e p e r c o u n ty g o v e rn m e n tlo g (v illa g e p e r T o w n ) lo g o f (N u m b e r o f v illa g e g o v e rn m e n t p e r to w n /to w n sh ip g o v e rn m e n t)lo g (# o f T o w n ) lo g o f (N u m b e r o f to w n , to w n sh ip s g o v e rn m e n t)

p a rty in d e xP o litic a l in d e x . T h e in te g ra tio n sc o re fo r p a rty se c re ta r ie s fro m 1 ( lo w e st) to 4 (h ig h e s t) . P le a se se e m o re d e sc rip tio n in D a ta S e c tio n in th e te x t.

M a rg in a l R e te n tio n R a te T h e m a rg in a l re te n tio n ra te o f lo c a lly c o lle c te d b u d g e ta ry re v e n u e (% )sh a rin g sc h e m e a , c , e , f S h a rin g S c h e m e (fro m a , c , e , f)(M R R X sc h e m e a ) (M R R X sc h e m e a )(M R R X sc h e m e c ) (M R R X sc h e m e c )(M R R X sc h e m e e ) (M R R X sc h e m e e )(M R R X sc h e m e f) (M R R X sc h e m e f)A g ric u ltu ra l p o p u la tio n A g ric u ltu ra l p o p u la tio n (1 0 th o u sa n d ) H o u se h o ld R e sp o n . F a rm R a tio H o u se h o ld re sp o n sib ility sys te m : th e p e rc e n ta g e o f p ro d u c tio n

te a m s in ru ra l a re a s th a t a d o p te d th e syste m (% )lo g (ro a d d e n sity p e r sq . k m ) lo g D e n sity o f ro a d (k m p e r sq k m )G ro ss d o m e stic p ro d u c t p e r c a p ita G ro ss d o m e stic p ro d u c t p e r c a p ita (yu e n )fo re ig n d ire c t in v e s tm e n t p e r c a p ita fo re ig n d ire c t in v e s tm e n t p e r c a p ita (yu e n )

Table 4: Data Summary TableObs Mean Std. Dev. Min Max

inter-provincial rural-rural non-hukou migrant 221 1.96 2.39 1.00 26.00TVE output 221 318388.00 427157.40 5915.98 2285719.00village/Town 221 13.84 5.47 6.65 35.79# of Town 221 2218.69 2947.61 206.00 20970.00party index 221 1.95 0.85 1.00 4.00Marginal Retention Rate (MRR) 221 44.93 44.48 0.00 100.00year 221 1984.46 1.30 1982.00 1986.00sharing scheme a 221 0.28 0.45 0.00 1.00sharing scheme c 221 0.06 0.24 0.00 1.00sharing scheme e 221 0.08 0.27 0.00 1.00sharing scheme f 221 0.14 0.34 0.00 1.00Household Respon. Farm. Team Ratio 221 91.69 19.65 0.00 100.00log(road density per sq. km) 221 0.19 0.11 0.01 0.53Urbanization Rate 221 26.54 15.32 9.93 65.13

Results:

• Lowest (village) level has strongest coefficient, and weakens as the level moves up

• Both labor sending (supply) and labor receiving (demand) provinces has expected sign. Position yourself!!

Gravity Model on inter-provincial Rural-Rural Non-Hukou Labor Migration (1982-1987)Model 1 Model 2

lrumij receving sending receving sendingCoef. Coef. Coef. Coef.

log(TVE output ) 0.29*** -0.20*** 0.33** -0.35***(0.1) (0.08) (0.15) (0.14)

log(village per Town) -0.90*** 0.32*** -1.12*** 0.46*(0.17) (0.13) (0.34) (0.26)

log(# of Town) -0.23*** 0.21*** -0.61*** 0.44**(0.07) (0.06) (0.25) (0.22)

party index -0.02 -0.02 -0.04 0.02(0.06) (0.05) (0.06) (0.05)

Household Respon. Farm Ratio 0.00 0.00 0.00 0.00(0.) (0.01) (0.) (0.)

(MRR X scheme a) -0.01** 0.00 -0.01 0.00(0.) (0.) (0.) (0.)

(MRR X scheme c) -0.01* 0.00 -0.01** 0.00(0.) (0.) (0.) (0.)

(MRR X scheme e) -0.01* 0.00 -0.01 0.00(0.) (0.) (0.) (0.)

(MRR X scheme f) 0.00 0.00 0.00 0.00(0.) (0.) (0.) (0.)

log(road density per sq. km) 0.13 -0.11 -0.01 -0.11(0.1) (0.09) (0.12) (0.09)

Constant 1.01 -1.10(2.44) (2.37)

Observations 221 221Centered R2 0.30 0.38Prob. > F Statistics 0 0Note: Heteroskedastic-consistent Standard Errors are in the parentheses.the interaction term in the model are: (MRR X scheme a, c, e, f, on receiving and sending provinces)All mdoel are Fixed Effects Model with Provincial GDP group dummies and year dummies***, **, * Significantly different from zero at the 1, 5, and 10 percent level respectivelyModel 2's control variables: gdp per capita, foreign direct investment per capita,log( agricutural output), log(agricultural population).

Evaluating the incentives of provincial level government:

T ab le 7 : R ela tive D ifferen cin g-in -D ifferen cin g o f P rov in cia l level F isca l D ecen tra liza tion im p acts to th e m od el

R e la tiv e D iff - in - D iff d iffe re n t in c o e ffic ie n t C h i2 (1 ) p -v a lu e

R e c e iv in g P ro v in c e s(M R R X sc h e m e a ) - (M R R X sc h e m e c ) -0 .0 0 5 5 .7 6 0 .0 2(M R R X sc h e m e a ) - (M R R X sc h e m e e ) -0 .0 0 4 3 .1 1 0 .0 8(M R R X sc h e m e a ) - (M R R X sc h e m e f) -0 .0 0 6 9 .7 9 0 .0 0(M R R X sc h e m e c ) - (M R R X sc h e m e e ) 0 .0 0 1 0 .1 9 0 .6 6(M R R X sc h e m e c ) - (M R R X sc h e m e f) -0 .0 0 2 0 .6 1 0 .4 4

S e n d in g P ro v in c e s(M R R X sc h e m e a ) - (M R R X sc h e m e c ) 0 .0 0 0 0 .0 0 0 .9 9(M R R X sc h e m e a ) - (M R R X sc h e m e e ) 0 .0 0 3 3 .2 4 0 .0 7(M R R X sc h e m e a ) - (M R R X sc h e m e f) 0 .0 0 2 1 .5 1 0 .2 2(M R R X sc h e m e c ) - (M R R X sc h e m e e ) 0 .0 0 3 1 .3 3 0 .2 5(M R R X sc h e m e c ) - (M R R X sc h e m e f) 0 .0 0 2 0 .8 0 0 .3 7N o te : th e c o e ffic ie n ts c o m p a re d h e re a re re g re ss io n re su lts e x tra c te d fro m c o lu m n 1 o f ta b le 6 .

Robustness Checking 1:(sub-sample of the data)

• Eliminating the subsidy provinces.

• Dropping provincial level institutional variables (Hausman test).

T ab le 8 : G rav ity M od el w ith su b -sam p lin g (n on -su b sid y p rov in ces)R e c e iv in g

P ro p o rtio n o f D a ta in S u b sid y P ro v in ces D e le ted in reg ressio n R e c e iv in g p ro v S e n d in g p ro v + S e n d in g p ro vV a ria b le s C o e f. C o e f. C o e f.lo g (T V E o u tp u t, re c e iv in g p ro v ) 0 .3 0 *** 0 .1 8 * 0 .1 9 *

(0 .1 2 ) (0 .1 1 ) (0 .1 3 )lo g (T V E o u tp u t, se n d in g p ro v ) -0 .1 9 ** -0 .2 5 *** -0 .2 6 ***

(0 .0 8 ) (0 .0 9 ) (0 .1 )lo g (v illa g e p e r T o w n , re c e iv in g p ro v ) -0 .9 7 *** -0 .8 4 *** -0 .8 0 ***

(0 .1 8 ) (0 .2 2 ) (0 .2 3 )lo g (v illa g e p e r T o w n , se n d in g p ro v ) 0 .3 9 *** 0 .4 1 *** 0 .5 0 ***

(0 .1 4 ) (0 .1 5 ) (0 .1 6 )lo g (# o f T o w n , re c e iv in g p ro v ) -0 .2 6 *** -0 .2 4 *** -0 .2 4 **

(0 .0 8 ) (0 .0 9 ) (0 .1 )lo g (# o f T o w n , se n d in g p ro v ) 0 .1 9 *** 0 .2 4 *** 0 .2 4 ***

(0 .0 6 ) (0 .0 9 ) (0 .1 )H o u se h o ld R e sp o n . F a rm R a tio , re c e iv in g 0 .0 0 0 .0 0 0 .0 0

(0 .) (0 .) (0 .)H o u se h o ld R e sp o n . F a rm R a tio , se n d in g 0 .0 0 0 .0 0 0 .0 0

(0 .0 1 ) (0 .0 1 ) (0 .0 1 )lo g (ro a d d e n s ity p e r sq . k m ), re c e iv in g 0 .1 5 0 .2 1 ** 0 .1 9 *

(0 .1 1 ) (0 .1 1 ) (0 .1 1 )lo g (ro a d d e n s ity p e r sq . k m ), se n d in g -0 .1 0 -0 .0 8 -0 .0 7

(0 .0 9 ) (0 .1 1 ) (0 .1 1 )C o n sta n t 1 .0 6 3 .5 2 2 .9 0

(2 .0 7 ) (2 .3 3 ) (2 .5 1 )N u m b e r o f o b se rv a tio n s 1 7 3 1 7 5 1 4 0C e n te re d R 2 0 .3 3 0 .3 4 0 .3 5P ro b > F S ta tis itic s 0 0 0N o te : H e te ro sk e d a s tic -c o n sis te n t S ta n d a rd E rro rs a re in th e p a re n th e se s . A ll m d o e l a re F ix e d E ffe c ts M o d e l w ith P ro v in c ia l G D P g ro u p d u m m ie s a n d ye a r d u m m ie s .U rb a n = C ity le v e l, R u ra l = T o w n + V illa g eC o n to rle d v a ria b le in c lu d e d : p a rty in d e x , th e in te ra c tio n te rm in th e m o d e l o f M R R X sc h e m e a , c , e , f, re sp e c tiv e ly o n re c e iv in g a n d se n d in g p ro v in c e s *** S ig n ific a n tly d iffe re n t fro m z e ro a t th e 1 p e rc e n t le v e l** S ig n ific a n tly d iffe re n t fro m z e ro a t th e 5 p e rc e n t le v e l. * S ig n ific a n tly d iffe re n t fro m z e ro a t th e 1 0 p e rc e n t le v e l

Robustness Check 2:

• Deal with missing data using “endogenous selection problem”: 3645 observations versus 221 observation

• Decomposes TVE output by a production function argument to see TVE’s investment effect to labor migration.

• Validate the claim of fiscal need by regressing provincial level expenditure on number of rural govts.

Selection regression model with endogenous selection

Model 1

lrumij receiving sending

  Coef. Coef.

log(TVE labor) -0.39* 0.15

(0.23) (0.22)

log(TVE investment ) 0.44* -0.45*

(0.25) (0.26)

log(land) 0.14 -0.18

(0.13) (0.12)

Predicted Rural Govt. Expenditure -0.99* 1.24***

(0.52) (0.45)

party index -0.01 -0.14**

(0.06) (0.07)

Household Respon. Farm Ratio 0.00 0.00

(0.) (0.01)

first stage (decision) model on both sides:  

gdp per capita yes

log(road density per sq. km) yes

log(village per Town) yes

log(# of Town) yes

party index yes

(MRR X scheme a) yes

(MRR X scheme c) yes

(MRR X scheme e) yes

(MRR X scheme f) yes  

No. of observation 221.00

Prob.>F 0.00

R-square 0.30  

Conclusion:

• Local economic development promote labor mobility

• Fiscal needs create incentive of promote labor mobility at labor sending provinces. But labor blockage for labor receiving provinces.

• Pressure from the lower level governments is highest because they are more connected their interest with TVEs’ development.

What is the policy implication?

Observations for non-Hukou migrant figures in 1 % 1990 Population census.

1990 Hukou status and current residence of working population (age 15-64)

Destination Type TotalMIGTYPE (second definition) city town villagelocal resid 1023342 627044 5979573 7629959Row % 13% 8% 78%perm mig, within prov 57487 32271 39923 129681Row % 44% 25% 31%perm mig, outside prov 21999 11946 16097 50042Row % 44% 24% 32%floater, >5yrs 20101 12832 17947 50880Row % 40% 25% 35%floater, within prov <5yrs 39272 18932 33836 92040Row % 43% 21% 37%floater, outside prov <5yrs 22533 10164 24308 57005Row % 40% 18% 43%Total 1184734 713189 6111684 8009607Row % 15% 9% 76%

Source: 1 % sample of the 1990 Chinese Population Census

Thank you!!Your comments are always

welcome!

ychen16@depaul.edu