09.13.2012 - Seema Jayachandran

165 views

Published on

The Price Effects of Cash Versus in-Kind Transfers

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
165
On SlideShare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
2
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

09.13.2012 - Seema Jayachandran

  1. 1. The Price Effects of Cash Versus In-Kind Transfers Jesse Cunha (Naval Postgraduate School) Giacomo De Giorgi (Stanford University) Seema Jayachandran (Northwestern University) September 2012
  2. 2. In-kind versus cash transfers• Government transfers are often made in-kind• One rationale is paternalism—boost consumption of certain goods• Other potential reasons are self-targeting, political economy• Weighed against constraining consumer choice and administrative costs• This paper: Price effects are another factor in this policy choice
  3. 3. Price effects of transfers• Cash and in-kind transfers have an income (demand) effect• Demand and prices for normal goods ↑• In-kind transfers also inject supply into the local economy – Setting where goods are provided (public housing) rather than vouchers (Food Stamps)• Influx of supply reduces prices⇒ This paper: Empirically assess the size of price effects for cashand in-kind transfers
  4. 4. Overview of paper• Examine price effects of food transfer program in Mexico – Randomized experiment across villages: in-kind transfers, cash transfers, control group• Find that prices decline for in-kind transfers relative to cash transfers• Larger effects in more remote villages, consistent with both... – More closed economy – Less competition• Magnitudes small in non-remote villages; large in remote villages• Differential effects for households that produce food
  5. 5. Effect of cash and in-kind transfers on prices P MC Supply provided by govt ΔPin‐kind  <   ΔPcash ΔPcash > 0 ΔPcash ΔPin‐kind Income effect MRin‐kind MR0 MRcash Q
  6. 6. Hypotheses• Cash transfers have positive income effect on prices ⇒ ∆pcash > 0• In-kind transfers have positive income effect + negative supply effect on prices ⇒ ∆pinkind < ∆pcash• Sign of ∆pinkind is theoretically ambiguous without restrictions on preferences – But for, e.g., homothetic preferences, ∆pinkind < 0
  7. 7. Imperfect competition• Can generate same predictions with imperfect competition – Cash transfers cause price increase – In-kind transfers cause prices to decrease, relatively• Effects probably more likely to persist in the long run under imperfect competition – Long-run supply curve flatter than short-run curve – If inherent barriers to entry lead to imperfect competition, may persist in long run
  8. 8. Normative implications of price effects• Lower price of transferred good furthers paternalistic goal of encouraging consumption of transferred goods• In-kind transfers redistribute from producers to consumers (relative to cash transfers)• If govt wants to tax producers to make transfers to consumers, in-kind transfers could be a second-best tax instrument (Coate, Johnson, and Zeckhauser 1994)• With imperfect competition, no longer just a pecuniary externality – Goods are undersupplied by the market – Govt influx of supply could increase efficiency
  9. 9. Outline of rest of talk• Background on PAL program + data• Results – Overall price effects for cash versus in-kind program – Heterogeneity based on remoteness of village – Quantifying the total effect – Producer versus consumer households• Conclusion
  10. 10. Transfer program we study• Mexico’s food assistance program, Programa de Apoyo Alimentario (PAL)• PAL nationwide (in 2009): 200,000 households in 5,000 villages• Targets poor households in villages too poor to be receiving Oportunidades
  11. 11. PAL experiment• Experiment in 2003-05: 208 villages• Village-level randomization among eligible villages (small, rural, poor) in 6 southern states• Household-level targeting: 89% of households eligible• 3 treatment arms – eligible HHs receive the following each month: – Food box with 10 goods – 150 pesos cash – No transfer (control group)
  12. 12. Items in food box Value per box Calories, as Village change Amount per (pre-program, % of total in supplyItem Type box (kg) in pesos) box (∆Supply) (1) (2) (3) (4) (5)Corn flour basic 3 15.7 20% 1.00Rice basic 2 12.7 12% 0.61Beans basic 2 21.0 13% 0.29Fortified powdered milk basic 1.92 76.2 17% 8.62Packaged pasta soup basic 1.2 16.2 8% 0.93Vegetable oil basic 1 (lt) 10.4 16% 0.25Biscuits basic 1 18.7 8% 0.81Lentils supplementary 1 10.3 2% 3.73Canned tuna/sardines supplementary 0.6 14.8 2% 1.55Breakfast cereal supplementary 0.2 9.3 1% 0.90Notes:(1) Value is calculated using the average of pre-treatment village-level median unit values. 10 pesos ≈ 1 USD.(2) ∆Supply measures the PAL supply influx into villages, relative to what would have been consumed absent theprogram. It is constructed as the average across all in-kind villages of the total amount of the good transferred to thevillage divided by the average consumption of the good in control villages in the post-period.(3) We do not know whether a household received canned tuna fish (0.35kg) or canned sardines (0.8kg); the analysisassumes the mean weight and calories throughout.(4) Biscuits are excluded from our analysis as post-program prices are missing.
  13. 13. Box of in-kind goods
  14. 14. PAL transfers being trucked into villages
  15. 15. Influx of cash and food was large• Transfers are large: 19% of baseline monthly food expenditures for recipients, 12% of total expenditures• Given 89% eligibility, influx of 17% of baseline monthly food expenditures for village• Cash transfer was 8% of baseline total expenditures for village
  16. 16. Income effect of transfers• Is the income effect from cash and in-kind transfers the same?• Could be smaller effect for in-kind transfers – recipients value the bundle less than its market value• Could be larger for in-kind transfers, e.g., transfer signals quality• Roughly, income effect is similar for both transfers in our setting
  17. 17. Equivalence of income effect for PAL program• Cost for the in-kind box at prices in village was 206 pesos• Government procurement cost was 150 pesos so set cash transfer at this amount• In-kind goods can’t be costlessly resold, so value is <206 pesos
  18. 18. What is value of PAL in-kind transfer?• 116 pesos of the bundle was inframarginal, based on examining control group’s consumption (Cunha 2012)• In-kind HHs consume 34 pesos more of these goods than they would have with cash transfer• Another 56 pesos of transfer is extramarginal but not consumed; transaction costs from resale• Assume deadweight loss erodes two thirds of value in both cases; 90 pesos nominal value but valued at 30 pesos• In-kind box valued at ∼146 pesos• Even if consumers only value the inframarginal portion, different income effect cannot explain magnitude of our results
  19. 19. Supply side of the market• Food is sourced from manufacturers outside these villages – We focus on only the local GE effects, ignoring possible Mexico- wide effects• Supply side within the village are grocery stores/shopkeepers• Agricultural producers in the village supply substitute goods
  20. 20. Village stores
  21. 21. Village stores
  22. 22. Data• Matched panel surveys of households and stores – Pre-intervention (2003) / Follow-up (2005) – Program underway for ≈ 1 year at follow-up – For HH survey, interviewed random sample of 33 HHs per village• 14 of 208 villages not included because of missing data or program began before baseline• Final sample: 194 villages, 360 stores• Randomization seems to have worked (Table 2)
  23. 23. Data on food prices• 9 PAL food items – 6 basic goods: corn flour, rice, beans, pasta, oil, fortified milk – 3 supplementary goods: canned fish, packaged breakfast cereal, and lentils – Data for 10th PAL good (biscuits) not collected• 51 non-PAL food items• No price data for non-food items
  24. 24. Price data• Our outcome variable is the good-store-village price (12,940 observations)• Price surveys of local stores in each village• Up to 3 stores per village but typically 1 or 2• Looked for, or asked for, lowest priced product• Incomplete baseline store data
  25. 25. Baseline price data: Unit values• Household survey has food consumption, expenditure, consumption out of own production by item, 7-day recall• We calculate unit values (expenditures per unit purchased)• Use median price for village-good• Interpolate from other villages in municipality if missing• Also use store prices, imputing missing values
  26. 26. Basic regression pgsv = α + β 1InKindv + β 2Cashv + φpgsv,t−1 + σXgv + gsv• g is good, s is store, v is village• Control for lagged prices• Control for indicator if lagged prices is imputed• Cluster on village• Two predictions are β 1 < β 2 and β 2 > 0
  27. 27. Effect of transfer program on price of PAL goods All PAL  Basic PAL  All PAL  Basic PAL  All PAL  Basic PA goods goods  goods goods  goods goods  Outcome =  price price price price price price (1) (2) (3) (4) (5) (6) In‐kind ‐0.037* ‐0.033 ‐0.036* ‐0.033 ‐0.032* ‐0.025 (0.020) (0.020) (0.020) (0.020) (0.017) (0.017) Cash 0.002 0.014 0.003 0.012 0.001 0.011 (0.023) (0.027) (0.023) (0.026) (0.020) (0.022) Lagged normalized unit value 0.027 0.127*** (0.021) (0.042) Lagged normalized store price 0.325*** 0.335** (0.052) (0.064) Lagged ln(unit value) Observations 2,335 1,617 2,335 1,617 2,335 1,617 Effect size:  In‐kind ‐ Cash ‐0.039** ‐0.047** ‐0.038** ‐0.045** ‐0.034** ‐0.036** H 0 :  In‐kind = Cash (p‐value) 0.02 0.04 0.03 0.04 0.03 0.04 Notes:  *** p<0.01, ** p<0.05, * p<0.1
  28. 28. Robustness checks• Results similar across specifications – Control for store prices – Use log prices• No evidence that results are driven by changes in quality
  29. 29. Heterogeneity based on remoteness of village• Two reasons to expect larger price effects in more remote areas – Less open economy (steeper supply curve) – Imperfect competition• Measured as travel time to market with fresh meat, vegetables, fruit – Use village median of self-reports in household survey
  30. 30. Results on remoteness of the village All PAL goods Basic PAL goods only Above‐ Below‐ Above‐ Below‐ median  median  All villages median  median  All villages remotenes remotenes remotenes remotenes Outcome =  price price price price price price (1) (2) (3) (4) (5) (6)In‐kind ‐0.030 ‐0.044* ‐0.050 ‐0.014 ‐0.045* ‐0.033 (0.033) (0.024) (0.030) (0.027) (0.027) (0.031)Cash 0.050 ‐0.029 0.013 0.062** ‐0.015 0.032 (0.034) (0.031) (0.031) (0.031) (0.038) (0.036)ln(Remoteness) x In‐kind ‐0.028 ‐0.007 (0.033) (0.036)ln(Remoteness) x Cash 0.023 0.033 (0.033) (0.037)Observations 865 1,470 2,130 603 1,014 1,471Effect size:  In‐kind ‐ Cash ‐0.081*** ‐0.015  ‐0.076*** ‐0.030 H 0 :  In‐kind = Cash (p‐value) 0.00 0.56 0.00 0.35Effect size:  ln(Remoteness) x In‐kind ‐ ln(Remoteness) x Cash ‐0.050** ‐0.040*H 0 :  ln(Remoteness) x In‐kind =  0.02 0.08ln(Remoteness) x Cash (p‐value)Notes:  *** p<0.01, ** p<0.05, * p<0.1(1) The outcome variable is the post‐treatment price; it varies at the village‐store‐good level. It is normalized by good; the price is divided by the average price of the good across all observations in the control group.  Standard errors are 
  31. 31. Testing between competition and closed economy explanations• Don’t have census of stores per village• Poor quality data when tried to collect it retrospectively in 2011• Suggestive evidence using number of stores in the data collection• Price effects persist for a year, even though long-run MC curve seems like it should be flat ⇒ Also suggests imperfect competition
  32. 32. Results on number of stores All PAL goods Basic PAL goods only Outcome =  price price price price (1) (2) (3) (4)In‐kind ‐0.030 ‐0.039 ‐0.018 ‐0.020 (0.058) (0.062) (0.064) (0.069)Cash 0.065 0.056 0.109 0.104 (0.067) (0.071) (0.071) (0.076)# stores x In‐kind ‐0.004 ‐0.006 ‐0.006 ‐0.007 (0.026) (0.025) (0.029) (0.029)# stores x Cash ‐0.032 ‐0.022 ‐0.047 ‐0.037 (0.028) (0.030) (0.030) (0.031)ln(Remoteness) x In‐kind ‐0.025 ‐0.006 (0.034) (0.037)ln(Remoteness) x Cash 0.022 0.026 (0.035) (0.038)Observations 2,130 2,130 1,471 1,471Effect size:  In‐kind ‐ Cash ‐0.095* ‐0.096* ‐0.127** ‐0.124**H 0 :  In‐kind = Cash (p‐value) 0.06 0.06 0.02 0.02Effect size:  # stores x In‐kind ‐ # stores x Cash 0.028  0.016  0.040* 0.030 H 0 : # stores  x In‐kind = # stores x Cash (p‐value) 0.15 0.47 0.05 0.18Effect size:  ln(Remoteness) x In‐kind ‐ ln(Remoteness) x Cash ‐0.047** ‐0.033 H 0 :  ln(Remoteness) x In‐kind = ln(Remoteness) x Cash (p‐value) 0.03 0.16Notes:  *** p<0.01, ** p<0.05, * p<0.1
  33. 33. Effects on non-PAL goods• Other food items are substitutes for PAL goods• Identify subset of goods that are close substitutes for PAL goods• Examine price effects for all other food items• No data for non-food prices
  34. 34. Substitutes Set of PAL substitutes All non‐PAL goods Above‐ Below‐ Above‐ Below‐ All villages median  median  All villages All villages median  median  All villages remoteness remoteness remoteness remoteness Outcome =  price price price price price price price price (1) (2) (3) (4) (5) (6) (7) (8)In‐kind ‐0.013 0.010 ‐0.024 ‐0.014 0.010 0.000 0.014 ‐0.005 (0.025) (0.032) (0.036) (0.029) (0.019) (0.029) (0.024) (0.023)Cash 0.027 0.035 0.024 0.024 0.009 0.039 ‐0.012 0.013 (0.031) (0.034) (0.045) (0.033) (0.022) (0.042) (0.023) (0.034)ln(Remoteness) x In‐kind ‐0.006 ‐0.022 (0.034) (0.028)ln(Remoteness) x Cash 0.002 0.014 (0.036) (0.032)Observations 1,442 498 944 1,307 10,648 3,765 6,883 9,698Effect size:  In‐kind ‐ Cash ‐0.039  ‐0.025  ‐0.048  0.001  ‐0.039  0.026 H 0 :  In‐kind = Cash (p‐value) 0.15 0.41 0.22 0.95 0.34 0.24Effect size:  ln(Remoteness) x In‐kind ‐ ln(Remoteness) x Cash ‐0.008  ‐0.036 H 0 :  ln(Remoteness) x In‐kind = ln(Remoteness) x Cash (p‐ 0.77 0.27value)Notes:  *** p<0.01, ** p<0.05, * p<0.1(1) The outcome variable is the post‐treatment price; it varies at the village‐store‐good level. It is normalized by good; the price is divided by the average price of the good across all observations in the control group.  Standard errors are clustered at the village level.(2) Regressions control for the main effects of the interaction terms reported, as well as for the pre‐period normalized unit value and an indicator for imputed pre‐program prices (see text).   
  35. 35. Magnitude of the effects• Multiply estimated change in prices by expenditure amount to quantify price effect in pesos• Expenditures per HH on PAL goods is 200 pesos and on non-PAL goods, 1050 pesos per month (in control villages)• Applies to non-recipients too• Price effects small for non-remote villages
  36. 36. Magnitude of the effects• Price effects have negligible effect on household purchasing power for non-remote villages• Price effects large in remote villages ⇒ Difference between in-kind and cash transfers equivalent to 60 extra pesos for a consumer (>30% of direct transfer)
  37. 37. Effects on food-producing households• HHs are mainly consumers of the PAL goods, but some HHs are agric. producers• Welfare effects differ for producers – e.g., Price increase from cash transfer is an extra benefit• Production decisions might respond to the program – e.g., Produce/sell more when prices rise in cash villages• Income effect also could affect production, e.g., investment affected if credit-constrained
  38. 38. Effects for food-producing HHs Farm  Farm ln(Expenditur ln(Expenditur Asset  Asset  Outcome =  profits  costs e per capita) e per capita) index index (1) (2) (3) (4) (5) (6)In‐kind 143.87 134.01 0.115** 0.084 (89.839) (119.511) (0.046) (0.075)Cash 186.16* 345.32** 0.064 ‐0.040 (106.082) (140.378) (0.052) (0.106)Producer x In‐Kind  0.001 ‐0.018 0.077 0.055 (0.060) (0.046) (0.115) (0.088)Producer x Cash 0.087 0.015 0.266* 0.229** (0.068) (0.051) (0.142) (0.109)Producer ‐0.161*** ‐0.003 ‐0.308*** ‐0.007 (0.050) (0.036) (0.092) (0.071)Control for pre‐period outcome? yes yes yes yes yes yesVillage FE yes yesObservations 4,924 5,038 5,534 5,534 5,571 5,571Effect size:  In‐kind ‐ Cash ‐42.29  ‐211.31* 0.050  0.124 H 0 :  In‐kind = Cash (p‐value) 0.67 0.08 0.25 0.20Effect size:  Producer x In‐Kind ‐ Producer x Cash ‐0.086  ‐0.033  ‐0.189  ‐0.174*H 0 :  Producer x In‐Kind = Producer x Cash (p‐value) 0.13 0.47 0.13 0.07Notes:  *** p<0.01, ** p<0.05, * p<0.1
  39. 39. Summary of findings• In rural Mexico, in-kind transfers cause prices of transferred goods to fall relative to cash villages• Results driven by more remote villages, perhaps because of less supply-side competition• In remote villages, in-kind transfers deliver 30% more to consumers than cash transfers• Welfare consequences of price changes are the opposite for producers – Price increase from cash transfers increases farm profits – Lower prices from in-kind transfers hurt farm profits
  40. 40. Concluding thoughts• Long-run effects might differ as supply adjusts• Many other considerations when choosing in-kind vs. cash transfers – Paternalistic goals versus constraining household choices – Govt may not be as efficient a supplier as the private sector• But price effects are too large to ignore in remote villages – High eligibility for social programs (typically ultra-poor) – Fewer stores – Less integrated with the outside economy• In-kind transfers are one tool to reduce oligopolistic inefficiencies

×