Sharing the wealth across the urban hierarchy in Sub-Saharan African countries: Resource rents and politics

Size: px

Start display at page:

Download "Sharing the wealth across the urban hierarchy in Sub-Saharan African countries: Resource rents and politics"

Bruno Greene
5 years ago
Views:

1 Sharing the wealth across the urban hierarchy in Sub-Saharan African countries: Resource rents and politics July 12, 2015 Vernon Henderson (LSE), Adam Storeygard (Tufts) and Jamila Nigmatulina (LSE)

2 Motivation: The Issues What drives the distribution of people across African cities? Are urban systems balanced and are secondary cities developing/prospering? High primacy (fraction of urban residents in largest city) in the raw data Although high in many non-sub-saharan African countries But Castells-Quintana (2015) suggests high primacy in Sub-Saharan African countries deters growth and tends to be excessive compared to Asian countries. To what extent is this primacy driven by policies and institutions, not by market forces? Related, major secondary cities in Sub-Saharan African countries growing more slowly than other cities. Why: Low manufacturing and little structural transformation?

3 Key possible policy/institutional factors 1. Role of natural resource rents Main cities as consumer cities : Jedwab et al (2015). Positive economics question: How are resource rents spent? Good to know, before advise on how they should be spent in a spatial context General budget for nationwide services: General (permanent) budget. How deal with fluctuating rents/royalties? Spread the extra dividend: Help all cities. (Collier and Venables, 2009) Versus political cities grab the extra goodies (big consumer cities) Interaction with democratization; also federalism Do we see political cities growing relatively faster or slower, with positive shocks to natural resource rents?

4 Other policies 2. Role of democratization Representative democracy gives voice to hinterlands Democratization is associated with fiscal decentralization Both may shift power from centre to the hinterlands [Fetzer and Shanghavi, 2015] Here must ask: What is interaction with resource rent shocks? 3. Trade agreements and exchange rates Loss of protection to local manufacturers Impact of resource rents on manufacturing exports (and exchange rates). Harding & Venables, 2013: $1 increase in resource export leads to $0.75 reduction in manufacturing exports Effect on larger secondary cities: actual or potential manufacturing centers. Other issues not considered here. Role of inter-city transport links and spatial bias in capital and export/import license allocations

5 African urbanization Urbanization is proceeding slowly, given cities are growing mostly just above natural population growth rates The annual growth of individual cities is 3-4% a year, modestly above population growth rate. Strong city growth but slower overall urbanization growth In some sense, have time to guide a better urbanization path. African has high primacy (explained by small country size and low level of urbanization)? Work by Castells- Qunitana (2015) suggests: Increases in primacy reduce growth in African countries, but increase it elsewhere Negative effect of primacy reduced in African countries with better urban infrastructure (sewer, water, electricity) Primacy excessive in 33 of 44 African countries, but only 17 of 39 Asian ones. Primacy is increasing

6 Data on cities Have nights lights annual data : all countries Measures economic growth (Henderson, Storeygard and Weil, 2012) Sample sizes of up to 1865 cities; use 1158 here (generally over today) Population census data: 2012 cross-section with projections from most recent census (2002 or later): 34 countries with population of about 550 million. Differences over time: 24 countries ; first and last censuses 1984, 2014 with population of about 450 million Source: Citypopulation.de; is based on census reports. Also for Nigeria supplement with Africapolis

8 Growth in 24 countries Cities over in 1990 and over in 2012 Same cut on relative size distribution (i.e., same cut-off: min to median size the same) Relative size distribution: very similar Transition matrix: either noisy data or a lot of churning

Population growth rates of cities: 1990-2012 Actual annualized growth rates between first and last census for each country: 819 cities Growth by type Median Mean N Primate 0.0376 0.

9 Population growth rates of cities: Actual annualized growth rates between first and last census for each country: 819 cities Growth by type Median Mean N Primate Below 100,000: non-political political Above 100,000: non-political political Low growth problem for larger secondary cities: lack of industrialization?

10 Manufacturing issue in Africa Based on the WDI (2013), between 1970 and 2000, the share of GDP in manufacturing increased in only 9 of 20 countries with relevant data (WDI, 2013). Many significant declines. From , 21 of 34 countries with relevant data saw actual decreases in their share of GDP in manufacturing; 16 of the original 20 had decreases. By 2010 only 3 of the 34 countries had manufacturing shares over 15%, with the majority under 8%. Role of resource rents and exchange rate appreciation: Do cities with high initial manufacturing base lose? Will look at for a few (4-8) African countries

11 Natural resource rent impacts on the urban hierarchy Effect on city growth in three dimensions Economic growth (proxy): Ln Annual night lights cities in 34 countries (with natural resource data). Cities with (projected populations) over 15, 000 in 1990 or over in Immediate and lagged responses to price changes To come: (1) Lights growth in initial high versus low manufacturing cities in response to resource price shocks sub-sample of 7-8 countries (2) Robustness: Annualized city population growth between census intervals {19 countries : 12 have 3 censuses; 7 have 2}. Longer term effects of longer term price swings

12 Urban hierarchy Urban hierarchy: two dimensions Political: (1) Primate city (effective national capital: Dodoma vs Dar Es Salaam) (2) Regional capital (19% of cities) (3) The rest Relative size In top 20% (excluding primate city) Or over 100,000

Income Data Outcome measure: growth in lights emitted at night Proxy for growth in economic activity (Henderson, Storeygard and Weil, 2012) Measures of economic activity are not available for

13 Income Data Outcome measure: growth in lights emitted at night Proxy for growth in economic activity (Henderson, Storeygard and Weil, 2012) Measures of economic activity are not available for cities Analysis unit: blobs of contiguous ever-lit 1-km pixels: Union (outer-envelope) of overlapping lights in from (must be lit in 2 or more years). Must have population. Ghana scene

14 Price shocks Shocks to resource rents: Price index: Sum of log of real commodity prices weighted by historical (77-83) (or ) share of that commodity export in country s GDP. 14 Mining-oil-gas commodities (petro, gold, natural gas, aluminum, copper, etc.) Crops for export (cotton, sisal, wheat, cocoa, tea, etc.) Price index = or ln Price index PE x ln P ; j : country; s, t : time; k :international commodity x kj 1983 EX kjt 1/ 7 ( ) GDP s l 1977 js P k ks x kj js js kj ks k jt Pkt t s l m Pks ; l : length of lag; m : length of smoothing. start m=1 and l =1 m PE is price variable for lights; Price shock (FD) = ( PE PE ) js js 1

15 Price series (also democratization)

16 Growth in lights formulation Lights as a function of PE, city FE, individual city time trend, and (country-) year FE First difference (cluster errors at city for serial correlation) Cities on a growth path. PE shocks move income up and down from that Therefore a one time permanent increase has no permanent effect on growth rate, but does raise income level. May have lag structure: assume effects start at t-1 May be differential effects for primate or regional capital Have mining/oil and (non-food) agriculture ln versus t k k light PE X PE ic, t j c, t j j i c, t j t i it j 0 j 0 X : indicators for primate and for regional capital tc

17 Results Effect of pure resource rent fluctuations Reduced form effects (to the extent resource rent shocks affect democratization or other channels, besides direct effects) May be a lag structure: First spend relatively more in political cities; then some evening up Shocks are not serially correlated (after city and time fixed effects, coefficient of lag difference on current difference is 0.02) 1 year effect (coefficient) 2 cumulative year effect (coefficients) City and year FE City and country-year FE City and year FE City and country-year FE Primate 2.61** 1.48** 1.25** Regional capitals 2.24** 1.73** 1.50** 0.89** 1 standard shift up in growth in price index (0.040): income up in regional capital up by 0.06 from a mean of ( given a (net) coefficient of 1.5). [0.036 for (net) coefficient of 0.89)

18 Growth in lights: First difference of ln lights (N= 22002; 1158 cities; Rsq s ) Basic Reg Added lag 4 periods PE(t-1-t-2) *** *** *** [0.179] [0.177] [0.185] PE*primate 2.613*** 1.483** 2.518*** 1.355* 2.496*** 1.442* [0.394] [0.742] [0.383] [0.751] [0.355] [0.747] PE*regional 2.228*** 1.734*** 2.176*** 1.675*** 2.263*** 1.793*** [0.400] [0.290] [0.404] [0.285] [0.427] [0.312] PE_lag2(t-2-t-3) 0.821*** 0.751*** [0.147] [0.148] PE_lag2*primate *** *** *** *** [0.237] [0.655] [0.253] [0.647] PE_lag2*regional cap ** *** ** *** [0.261] [0.253] [0.253] [0.252] PE_lag *** PE_lag3*primate *** PE_lag3*regional cap *** * PE_lag * PE_lag4*primate PE_lag4*regional cap [0.243] [0.246] Observations 22,002 22,002 22,002 22,002 22,002 22,002 Number of city_id 1,158 1,158 1,158 1,158 1,158 1,158 City FE YES YES YES YES YES YES Country-Year FE YES YES YES Time FE YES YES YES

19 Size Effect Agriculture price shocks PE(t-1-t-2) *** *** *** [0.194] [0.192] [0.178] PE*primate 2.736*** 2.640*** 2.610*** 1.488** [0.400] [0.389] [0.390] [0.743] PE*regional 1.717*** 1.665*** 2.224*** 1.738*** [0.511] [0.515] [0.400] [0.290] PE_lag2(t-2-t-3) 0.824*** *** [0.148] [0.178] PE_lag2*primate *** [0.238] PE_lag2*regional cap ** [0.263] City in top 20% of size * PE 1.009*** 1.005*** [0.320] [0.319] D_top20%* PE_lag [0.0437] PE agricultural price index [0.465] PE ag*primate [1.016] [0.613] PE ag*regional cap 1.078** 1.095* [0.526] [0.599]

20 Heterogeneity: political economy Examine effect of sustained democratization in Africa over last 20 years Democratization Annual polity 2 measures (-10, 10). Regime switches: wave of democratization in early 1990 s with more around But, majority no change Fetzer and Shanghavi (2015): Lights and school completion rise in regional capitals and other cities relative to primate after democratization Define as democracy if Switch to democracy in first year polity 2 2, as long as not less than 0 for 20% of remaining years to 2012 (Bai et al) Current democracy =1 if polity 2 2 in current year

21 In essence what we do: Smoothed indicator vs actual score: Burundi (Bai, 1997)

22 Growth in lights: First difference of ln lights (N= 22002; 1158 cities; Rsq s ) Basic Reg Added lag 4 periods PE(t-1-t-2) *** *** *** [0.179] [0.177] [0.185] PE*primate 2.613*** 1.483** 2.518*** 1.355* 2.496*** 1.442* [0.394] [0.742] [0.383] [0.751] [0.355] [0.747] PE*regional 2.228*** 1.734*** 2.176*** 1.675*** 2.263*** 1.793*** [0.400] [0.290] [0.404] [0.285] [0.427] [0.312] PE_lag2(t-2-t-3) 0.821*** 0.751*** [0.147] [0.148] PE_lag2*primate *** *** *** *** [0.237] [0.655] [0.253] [0.647] PE_lag2*regional cap ** *** ** *** [0.261] [0.253] [0.253] [0.252] PE_lag *** PE_lag3*primate *** PE_lag3*regional cap *** * PE_lag * PE_lag4*primate PE_lag4*regional cap [0.243] [0.246] Observations 22,002 22,002 22,002 22,002 22,002 22,002 Number of city_id 1,158 1,158 1,158 1,158 1,158 1,158 City FE YES YES YES YES YES YES Country-Year FE YES YES YES Time FE YES YES YES

23 Democratization PE (t-1-t-2) 1.662*** [0.521] PE*primate [0.680] [1.042] PE*regional [1.095] [1.039] demoswitch 0.114*** 0.853*** [0.0152] [0.266] dem_primate *** [0.0270] [0.0318] dem_regional *** [0.0190] [0.0217] dem* PE *** [0.577] dem* PE*primate 3.468*** 2.544** [0.871] [1.068] dem* PE*regional 2.868** [1.133] [1.064] Observations 22,002 22,002 R-squared Number of city_id 1,158 1,158 City FE YES YES Country-Year FE YES Year FE YES Looks like In non-democratic countries no resource rent effects for political cities relative to other cities. In democratic, rents spent in primate and regional capitals relative to other cities Extra lags add little Issues In non-democratic in general is there just no visible effect (money disappears, goes to ethnic group related to President). While in democratic, at least spend in political cities. Democracy is not always decentralization: need separate measure

24 Distribution of population across cities over 23,000 in 2012

25 .15 Continuous PDFs, normalized by median Relative size distribution: 2012 loss in outer tail (over 0.75)? Peak at smaller relative size Graph is for common set of cities which are both over in 1990 and in Log relative to median PDF in 1990 PDF in 2012

26 Transition matrix Cell shares: 1990: 35, 30, 20, 10 & 5% versus 2012: 30, 36, 20, 9.5 & 5.0 %

27 Preliminaries: Cross-Section: ln Population projected, 2012 primate 3.882*** 3.866*** 3.906*** [0.144] [0.146] [0.148] regional capital 1.027*** 0.991*** 1.009*** [0.0677] [0.0688] [0.0692] primate* avg PE_ ** ** [0.0712] [0.0718] [0.0739] regional cap*avg PE_ *** *** *** [0.022] [0.0224] [0.0335] Avg polity_98-07*primate [0.0359] [0.0376] Avg polity_98-07*regional cap *** * [0.0174] [0.0186] primate* avg PE_9807* avg_polity_ * [0.0203] regional cap* avg PE_9807* avg_polity_ ** [0.0095] Observations 1,075 1,075 1,075 R-squared Number of country_id Country FE YES YES YES Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 Cross section suggests Higher resource rents associated with smaller primate and regional capitals, compared to the base Democratization associated with larger regional capitals

AFRICAN URBANIZATION: SOME KEY ISSUES. Patricia Jones University of Oxford IGC Conference, Dar es Salaam 25 th February 2015

AFRICAN URBANIZATION: SOME KEY ISSUES Patricia Jones University of Oxford IGC Conference, Dar es Salaam 25 th February 2015 Introduction New project on urbanization in Africa. World Bank funded but independent