Efficiency and Regulation: The Case of Ontario and New York Dairy Farms

Transcription

1 Efficiency and Regulation: The Case of Ontario and New York Dairy Farms Peter Slade & Getu Hailu University of Guelph July 1, 2011

2 Motivation Ongoing public and academic debate regarding supply management See Goldfarb (2009); Robson and Busby (2010); Barichello, Cranfield and Meilke (2009)

3 Dairy Farm Policy Canada Pricing formula Quantity restrictions Import restrictions

4 Dairy Farm Policy Canada Pricing formula Quantity restrictions Import restrictions United States Marketing orders Price support Countercyclical subsidy Import Restrictions

5 Producer subsidy equivalents Figure: Producer Subsidy Equivalent for Canadian and US Dairy

6 Theoretical Implications Production decisions based on rules of thumb, changed only when shown to be sub-optimal (Winter, 1971)

7 Theoretical Implications Production decisions based on rules of thumb, changed only when shown to be sub-optimal (Winter, 1971) Natural selection through competition

8 Existing literature Haghiri, Nolan and Tran (2003) Use same datasets ( ) Calculate technical efficiency using a nonparametric stochastic frontier model

9 Existing literature Haghiri, Nolan and Tran (2003) Use same datasets ( ) Calculate technical efficiency using a nonparametric stochastic frontier model Other studies include: Weersink et al (1990), Tauer (1993 and 1996), Hailu et al (2005) and Mosheim and Lovell (2009)

10 Data Time period:

11 Data Time period: Sources

12 Data Time period: Sources Subsampling

13 Data Time period: Sources Subsampling Variables Output: milk, crops & livestock Input: feed, labour, capital & other

14 Descriptive statistics New York Ontario Mean dairy cows per farm Mean output per cow (liters) 8,635 8,096 Mean milk price ($CAD) Mean crop revenue ($CAD) 10,024 25,306 Livestock revenue per cow ($CAD) Mean purchased feed per cow ($CAD) 1, Mean labour quantity index per cow Mean physical assets ($CAD) 988,145 1,366,125 Mean physical assets per cow ($CAD) 9,303 20,259 Mean other quantity index per cow

15 Empirical Strategy Data envelopment analysis (3 models)

16 Empirical Strategy Data envelopment analysis (3 models) 1 Pooled model

17 Empirical Strategy Data envelopment analysis (3 models) 1 Pooled model 2 Separated model

18 Empirical Strategy Data envelopment analysis (3 models) 1 Pooled model 2 Separated model 3 Intermediate model: uses additional reference years which have similar technology

19 Empirical Strategy Data envelopment analysis (3 models) 1 Pooled model 2 Separated model 3 Intermediate model: uses additional reference years which have similar technology Econometric estimation of the distance function

20 Data Envelopment Analysis

21 Data Envelopment Analysis

22 Data Envelopment Analysis Technical efficiency = OA OB

23 Data Envelopment Analysis Cost efficiency = OC OB Allocative efficiency = (Cost efficiency) / (Technical efficiency)

24 Bootstrapping

25 Bootstrapping

26 Bootstrapping ˆθ (x, y) ˆθ(x, y) ˆρ(χ n ) ˆθ(x, y) θ(x, y) ρ. (1)

27 Econometric Estimation J K T ln δ it = C + α j ln y itj + β k ln x itk + γ t ln td it + u it (2) j=1 k=1 t=1 J K T ln x it1 = C + α j ln y itj + β k ln(x itk /x it1 )+ γ t ln td it +e it where: j=1 k=2 t=1 (3) e it = u it ln δ it (4) Duality is used to derive the cost function and cost efficiency scores analytically

28 DEA results Table: Weighted Average Efficiency Scores from Separated Model (Non-corrected scores in parenthesis) Technical Eff Allocative Eff Cost Eff New York (0.885) (0.912) (0.809) Ontario (0.832)*** (0.736)*** (0.609)*** Overall (0.868) (0.855) (0.744) Non-corrected scores are in parenthesis. *, **, **** represent significant differences between regions at the.1,.05 and.01 levels.

29 Econometric Results Table: Results From ML Estimation Coefficient Standard Error Milk *** Livestock *** Crop *** Labour *** Capital *** Other *** σ *** γ ***

30 Econometric Results (ctd.) Table: Weighted Average Efficiency Scores from Parametric Estimation Technical Eff Allocative Eff Cost Eff New York Ontario 0.933** 0.734*** 0.684*** Total *, **, **** represent significant differences between regions at the.1,.05 and.01 levels.

31 Triangulation Table: Correlation and Rank Correlation of DEA and Econometric Efficiency Scores Correlation Rank Correlation Technical Allocative Cost

32 Input usage Table: Change in Input Usage Necessary to Achieve Cost Efficiency Feed Labour Capital Other New York -21.4% -18.2% -29.7% -14.6% Ontario 64.2% -26.6% -61.4% -39.9%

33 Explaining efficiency Technical Efficiency Allocative Efficiency Estimate Standard Estimate Standard error error Ontario -4.28e e-03*** -2.61e e-02*** # of cows -9.34e e e e-04 Age -1.86e e-04*** -1.28e e-04** Education 9.24e e e e-02 Tie-stall -1.45e e e e-02 Pipeline -1.88e e e e-02** Parlour -1.40e e e e-02 bst 3.52e e e e-06***

34 Does scale matter? Number of cows not significant Scale efficiency Ontario % New York % Overall %

35 Conclusions

36 Conclusions Ontario farms less allocatively efficient than New York farms

37 Conclusions Ontario farms less allocatively efficient than New York farms Ontario farms are overcapitalized, relying too heavily on homegrown feed

38 Conclusions Ontario farms less allocatively efficient than New York farms Ontario farms are overcapitalized, relying too heavily on homegrown feed Both empirical techniques have the same broad findings across regions, through the correlation between them is very low

39 Conclusions Ontario farms less allocatively efficient than New York farms Ontario farms are overcapitalized, relying too heavily on homegrown feed Both empirical techniques have the same broad findings across regions, through the correlation between them is very low Scale is not a major differentiator

40 Thank you

41 Data Envelopment Analysis Define the production possibilities set ˆΨ =(x, y) R N+M (5) where y x n λ i y i i=1 n λ i x i i=1 λ i 0fori =1, 2...n. λi = 1

42 Data Envelopment Analysis (ctd) Measure technical efficiency Measure cost efficiency where ˆθ(x, y) =inf{θ (θx, y) ˆΨ}. (6) CostEfficiency i = C i. (7) C i C i (y i, w i )=min{w i x x ˆΨ}. (8)

43 Econometric estimation Econometric estimation of the distance function D i (X, Y )=max{δ i :(X /δ i, y)ψ} (9) θ i =1/δ i (10)

44 Concept of efficiency Technical efficiency

45 Concept of efficiency Technical efficiency Cost efficiency

46 Concept of efficiency Technical efficiency Cost efficiency Allocative efficiency = CE / TE