missed opportunities and missing markets: spatio-temporal arbitrage of rice in madagascar

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Missed opportunities and missing markets: Spatio-temporal arbitrage of rice in Madagascar. Christine Moser, Chris Barrett and Bart Minten  May 18, 2005 World Bank seminar. Motivation. Markets are crucial for -transmitting macro/sectoral policy signals to micro-level agents - PowerPoint PPT Presentation

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Missed opportunities and missing markets:

Spatio-temporal arbitrage of rice in Madagascar

     

Christine Moser, Chris Barrett and Bart Minten May 18, 2005

World Bank seminar

Motivation

Markets are crucial for -transmitting macro/sectoral policy signals to micro-level agents- maintaining incentives in the face of technological change - managing locally covariate risk

Yet we know surprisingly little about: - how markets function - the correlates of markets which are competitive, non-competitive, or segmented- scales at which policy interventions ought to occur

This paper addresses these gaps using data from Madagascar.

rit=rjt + ijtSpatial competitive equilibrium (1)

ri(t+1)=rit +

Intertemporal competitive equilibrium (2)

rit =pit + Processing competitive equilibrium (3)

Competitive marketing equilibrium conditions with

trade

Where r is rice price, p is paddy price, τ is spatial marketing margin, π is storage and interest costs, and α is milling costs.

Thus,

pit = rj(t+1)--jit- Integrated food marketing system eqln (4)

rit=rjt + ijtRegime 1: Competitive tradable

equilibrium

|rit-rjt| < ijtRegime 2: Competitive segmented

eqn

|rit-rjt| > ijtRegime 3: Non-competitive equilibrium /disequilibrium

But competitive equilibrium doesn’t always hold…

Baulch (1997 AJAE) and Barrett and Li (2002 AJAE) develop appropriate mixture distribution-based ML methods – parity bounds model (PBM) – for estimating the probability that markets are in one or another regime.

 

PBM (Parity Bounds Model)

0

5000

10000

15000

20000

25000_stack

1 1 1 1 2 2 2 2 3 3 3 3 3 4 4 4 4 Quarter 1 Quarter 2 Quarter 3 Quarter 4

Pri

ce D

iffere

nce (

ab

solu

te)

Regime 3: Non-competitive/ disequilibrium

Regime 1: Competitive eqlnRegime 2: Segmented eqln

Policy Implications Vary By Regime

Regime 1: laissez faire, perhaps work to reduce marketing margins

Policy interventions most appropriate under:Regime 2: marketing margins a binding constraint

on market-based transmission of policy signals, diffusion of local risk, incentives to adopt improved technologies.

Regime 3: market competition a constraint on market-based transmission of policy signals, diffusion of local risk, incentives to adopt improved technologies.

Market Integration

Methods

• Model of trader entry. Basic model of trader entry into a market given prevailing transport costs, access to finance, and other commune characteristics.

• Estimation of Parity Bounds Model (PBM) by MLE. This produces the probability that the market is integrated. The PBM is used to test spatial and intertemporal integration as well as integration across space, time and form.

• Explaining non-integration. Using the PBM results, estimate a multinomial logit to examine the factors affecting whether a market is integrated (Regime 1), non-trading (Regime 2), or non-competitive (Regime 3).

 

Boundaries:

Provincial

Fivondronona (sub-regional)

Commune

Cities

Capital

Provincial capital

Other major cities

Antsiranana

Toamasina

Mahajanga

Toliara

Morondava

Fort Dauphin

Fianarantsoa

Antsirabe

Antananarivo

Data Source:2001 commune census

• Rice & paddy prices for 4 quarters

• Rainy & dry season transport costs for products to different destinations.

• Also: imported rice prices, whether commune exports rice to other areas, access to public goods and services, types of economic activity, and climate variables.

National Sub-regional

Regional

Three scales of spatial market integration

Quarter 1: pre harvest

Quarter 2: harvest

Rice price/kg in FMG

The Commune CensusDry season cost of transporting 50kg

to major city

Results: Spatial Market Integration

Sub-regional  Regional 

 National 

Coeff. Std Error

Coeff. Std Error

Coeff. Std Error

Regime 1 0.689 0.0249

0.055 0.0245 0.128 0.0276

Regime 2 0.215 0.0194 0.311 0.0228 0.830 0.0301

Regime 3 0.096 0.634 0.043

E 1.512 1.91 1.530 3.11 0.025 1.76

U 8.623 7.35 5.989 4.98 3.894 2.13

V 4.39 11.65 1.003 5.03 0.241 4.28

(unobserved costs,FMG/kg)

8.257 9.04 27.619

14.05 18.238

9.72

N 4930 5070 5070

Table 4: Spatial PBM Estimation Results

Explaining Spatial Market Integration

Table 5 Spatial market regimes—Sub-regional level Multinomial logit

with sub region fixed effects Regime 2

(Segmented) Regime 3

(Non-competitive) Regime 1 is comparison group Coeff. Std Error Coeff. Std Error High crime area (dummy) -0.074 -0.750 0.462 2.850 Bank (dummy) -0.038 -0.170 0.618 1.720 Same ethnic group as town (dummy) 0.060 0.440 0.463 2.210 Travel time (log of hrs) to town 0.450 10.260 0.188 2.690 No motorized transport (dummy) -0.071 -0.640 0.584 3.070 Mean income (log of Fmg) -0.272 -1.250 -2.127 -5.150 Population (log) -0.002 -0.700 0.006 1.330 Percent working in agriculture -0.103 -1.310 -0.045 -0.330 Radio reception (dummy) 0.083 0.850 -0.326 -1.920 April-June (dummy) -0.170 -1.440 0.063 0.420 July-September (dummy) 0.271 2.440 -1.435 -6.990 October-December (dummy) 0.357 3.240 -1.441 -6.960 Constant 2.908 0.980 23.868 4.280 N= 4089 2= 1104 Log likelihood value = -2810.08 Pseudo R2= 0.164

Intertemporal Market Integration

(between the second and third quarters)

Table 7: Intertemporal PBM estimation results

Rural Town/city

 

Coeff. Std Error Coeff. Std Error

Regime 1 0.061 0.023 0.114 0.011

Regime 2 0.556 0.019 0.872 0.017

Regime 3 0.383 0.014

2.293 0.121 2.594 0.018

U 1.772 0.106 1.677 0.029

V 0.933 0.085 1.243 0.023

Unobserved costs (%/quarter)

0.972 0.020 0.321 0.014

N 1239 98

Chi-squaredP(Chi-sq > value

75600.000

3900.000

Table 8 Intertemporal market regimes Multinomial logit

with region fixed effects Regime 2

(Segmented) Regime 3

(Non-competitive) Regime 1 is comparison group Coeff. Std Error Coeff. Std Error High crime area (dummy) 0.053 0.210 0.212 0.780 Bank (dummy) -1.092 -2.260 -1.162 -2.110 Same ethnic group as city (dummy) -0.372 -1.530 -0.130 -0.510 Travel time (hrs) to city 0.019 0.190 0.190 1.760 No motorized transport (dummy) -0.796 -2.850 -0.197 -0.690 Mean income (Fmg) 0.958 2.160 -0.226 -0.480 Population (log) 0.197 0.990 0.459 2.180 Percent working in agriculture 0.012 1.740 0.005 0.670 Radio reception (dummy) 0.225 0.920 0.256 1.000 Fianarantsoa -0.077 -0.230 0.902 2.800 Toamasina 1.938 3.040 1.589 2.420 Toliara 1.237 2.730 -0.386 -0.730 Mahajanga 0.990 2.620 0.018 0.040 Diego 0.672 1.430 0.415 0.800 Antsirabe 0.221 0.370 1.162 1.990 Morondava 1.831 1.720 1.457 1.330 Fortdauphin 1.294 2.240 -0.367 -0.530 Constant -12.994 -2.120 -1.007 -0.160

Explaining Intertemporal Market Integration

 

Interseasonal flow reversals

Low Season Harvest Season

Quarter 1: pre harvest

Quarter 2: harvest

Price Difference (local – city)

Rural Town/city Rice price Oct-Dec 2000 2,525.81 2,468.26 Rice price Jan-March 2001 2,558.69 2,517.15 Rice price April-June 2001 1,780.85 2,156.88 Rice price July-Sept 2001 1,953.81 2,012.50 Percentage change in rice price 85.40 64.73

Table 10 Flow reversals Probit =1 if flow reversal is feasible Coeff. Std Error High crime area (dummy) 0.171 1.880 Bank (dummy) -0.026 -0.120 Same ethnic group as town (dummy) -0.171 -1.940 Travel time (log of hrs) to town -0.169 -4.590 No motorized transport (dummy) 0.065 0.600 Mean income (log of Fmg) 0.162 0.970 Population (log) 0.137 1.920 Percent working in agriculture 0.005 1.890 Radio reception (dummy) -0.168 -1.900 Fianarantsoa -0.074 -0.590 Toamasina -0.435 -2.730 Toliara -0.362 -2.280 Mahajanga -0.076 -0.560 Antsiranana -0.264 -1.610 Antsirabe 0.142 0.730 Morondava -0.105 -0.410 Fortdauphin -0.372 -1.800 Constant -3.218 -1.400 N= 1049 2= 59.23 Log likelihood value= -691.82 Pseudo R2= 0.041

Market integration across space, time and form

Sub-regional Level Regional Level

Coeff. Std Error Coeff. Std Error

Regime 1 0.793 0.014 0.000 0.019

Regime 2 0.052 0.014 0.045 0.003

Regime 3 0.155 0.955

4.062 0.047 0.543 0.011

U 1.318 0.034 0.532 0.008

V 1.087 0.067 0.686 1.71

Unobserved costs (%/quarter)

1.947 0.059 0.073 0.028

1104 1136

Chi-squaredP(Chi-sq > value)

70090.000

509750.000

Summary of Results and Implications

• Markets are fairly well integrated spatially and across time, space and form at the local/sub-regional level.

• At regional level, markets are largely non-competitive or in disequilibrium … need competition policy and foster market entry by traders (info, finance, crime, etc.)

• At the national level, transportation costs are generally so high as to preclude spatial arbitrage … transport key.

•Interseasonal storage is generally unprofitable due, it appears, to high unobserved storage/interest costs.

•Crime and isolation tend to reduce spatial integration.

Thank you for your comments and interest

Table 2 Rice prices and transport costs Rural Town/city Total

Rice price Oct-Dec 2000 (Fmg/kg) 2,525.81 2,468.26 2,521.78 (1,024.26) (487.42) (996.13) Rice price Jan-March 2001 (Fmg/kg) 2,558.69 2,517.15 2,555.77 (979.28) (691.55) (961.77) Rice price April-June 2001 (Fmg/kg) 1,780.85 2,156.88 1,807.18 (982.43) (2,113.64) (1,102.89) Rice price July-Sept 2001 (Fmg/kg) 1,953.81 2,012.50 1,957.92 (520.41) (402.13) (513.11) Percentage change in rice price 85.40 64.73 83.96

(from min to max across four quarters) (67.10) (46.47) (66.06) Transport cost to major city (Fmg/kg) 319.09 253.10 314.49 (414.52) (259.09) (405.90)

Table 3. Correlation coefficients Rice Price Oct-Dec

2000 Jan-March

2001 April-June

2001 July-Sept

2001 Jan-March 0.78 April-June 0.11 0.13 July-Sept 0.50 0.38 0.26 Quarterly paddy price 0.42 0.63 0.79 0.74 Quarterly imported rice price 0.92 0.91 0.16 0.26 Sub-region price 0.20 0.44 0.54 0.50 Region price 0.19 0.38 0.21 0.42

Table 6 Spatial market regimes—Regional level Multinomial logit

with region fixed effects Regime 2

(Segmented) Regime 3

(Non-competitive) Regime 1 is comparison group Coeff. Std Error Coeff. Std Error High crime area (dummy) -0.321 -2.040 -0.086 -0.580 Bank (dummy) 0.509 1.100 0.632 1.450 Same ethnic group as city (dummy) 0.867 1.420 0.931 1.540 Travel time (hrs) to city 0.494 7.550 0.083 1.370 Mean income (Fmg) -0.025 -0.090 -0.159 -0.570 Population (log) 0.048 0.400 0.107 0.940 Percent working in agriculture 0.005 1.220 0.010 2.630 No motorized transport (dummy) 0.111 0.620 0.025 0.140 Radio reception (dummy) 0.168 1.110 0.308 2.150 April-June (dummy) 0.026 0.130 0.550 2.880 July-September (dummy) 0.067 0.370 -0.151 -0.880 October-December (dummy) 0.201 1.060 0.160 0.890 Fianarantsoa 0.506 2.210 0.148 0.670 Toamasina 1.356 3.290 0.839 2.050 Toliara -0.804 -3.000 -0.057 -0.230 Mahajanga -0.812 -3.350 -0.229 -1.000 Antsiranana -1.477 -5.430 -0.537 -2.210 Antsirabe -1.068 -3.600 -0.939 -3.600 Morondava 0.789 1.430 0.489 0.900 Fortdauphin 0.675 1.470 0.821 1.850 Constant 0.212 0.050 2.514 0.650

N=47162=528.1

LL value = -3576.85Pseudo R2=0.069

Table 9 Difference between sub-region price and commune price

Sub-regionPercent of communes with:

Jan-March

HarvestApril-June

July-Sept

Oct-Dec

Higher price than town (rit-rjt

>0) 49% 26% 33% 43%

Lower price than town (rit-rjt

<0) 37% 59% 44% 32%

Price equal to town (rit-rjt =0) 14% 15% 23% 25%

Region

Higher price than town (rit-rjt

>0) 44% 21% 31% 36%

Lower price than town (rit-rjt

<0) 43% 69% 49% 47%

Price equal to town (rit-rjt =0) 13% 10% 19% 17%

Price Spans

0

500

1000

1500

2000

2500

3000

3500

4000

1 2 3 4

Figure 2. Rice price by quarter (Spans are trimmed at the 5 th and 95 th percentiles)

Ric

e P

rice

(F

mg/

kg)

Figure 3. Median and span of price differences at the regional level (Spans are trimmed at the 5th and 95th percentiles)

-2000

-1500

-1000

-500

0

500

1000

1500

1 2 3 4 Quarter

Pri

ce D

iffe

renc

e pe

r kg

in F

mg

(rit-

r jt)

Communes for which walking or traveling by ox cart is

necessary

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