1 / 70

Productivity Growth in Agriculture in Latin America and the Caribbean

Productivity Growth in Agriculture in Latin America and the Caribbean. Presented by Carlos Ludena. Outline. Importance of Agricultural Productivity Methods to Measure Total factor Productivity Productivity in Agriculture - Results Agricultural Productivity in Latin America

azizi
Download Presentation

Productivity Growth in Agriculture in Latin America and the Caribbean

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Productivity Growth in Agriculture in Latin America and the Caribbean Presented by Carlos Ludena

  2. Outline • Importance of Agricultural Productivity • Methods to Measure Total factor Productivity • Productivity in Agriculture - Results • Agricultural Productivity in Latin America • Impacts of External Shocks and Economic Reforms • Going forward – future analysis

  3. I. Agricultural Productivity - Importance to the wider economy

  4. Productivity in Agriculture • Agricultural productivity is an key factor for agricultural development. • Agricultural development is an important precondition towards industrialization • Preceded and promoted industrialization in now developed economies. • Agricultural productivity growth is higher relative to manufacturing (Martin and Mitra, 1999) • 0.5 - 1.5 percent per year higher

  5. Agricultural Productivity and economic growth • Agricultural productivity improves broader economic growth by: • Generation of additional demand for goods and services produced outside agriculture as income from agriculture increases. • Savings through increased farm incomes which can then be invested both in agriculture and other sectors. • Release of labor to the industrial sector. • Provision of cheap food for urban areas, enabling them to maintain wage rates at competitive levels • Provision of raw material to support manufacturing.

  6. II. Approaches to Measure TFP - Distance functions and the Malmquist Index

  7. Total Factor Productivity (TFP) • Can take into account all relevant factors and offer a more detailed view relative to partial factor productivity (PFP) • Used in the analysis of agricultural productivity

  8. TFP Measurement Approaches • Frontier or Non-Frontier • Frontier approaches explicitly incorporate inefficiency and account for changes in efficiency over time. • Non-frontier approaches generally assume that observed output is frontier output • Competitive optimizers behavior. Firms are technically efficient • TFP is changes in production technology only

  9. TFP Measurement Approaches • Econometric • Estimation of cost and production functions (non-frontier) • Estimation of production frontier • Deterministic • Index Numbers (Laspayres, Paasche, Törnqvist) • Mathematical Programing (Malmquist Index)

  10. TFP Measurement Approaches

  11. Deterministic Methods • Do not involve explicit specification of a production function (no estimation of parameters) • A deterministic or exact relationship between inputs and outputs. • Sensitive to measurement errors

  12. B A y2 g C P(x) y1 O2 O Output Possibility Set and Distance Functions P(x)= {y  R+M | (y, x)  S} D0(x, y) = (sup{θ: (x, θy)  S})-1 θ = Efficiency coefficient D0(x, y) = OC/OA

  13. Distance Functions and Productivity Indices y2 Bt+1 Bt At+1 g At St St+1 y1 O

  14. Malmquist Index • Malmquist Index (Caves et al., 1982) Maximal proportional change in output to make (xt,yt) feasible in relation to technology at t+1. Technology in period t is reference technology. Technology in period t+1 is reference technology.

  15. TFP, Malmquist Index and Distance Functions • Fare et al. (1994, AER): Geometric mean of two Malmquist Indexes (t and t+1) • Shepard’s Distance Function: • Maximum proportional change in outputs required to make the set of input and outputs feasible in relation to the technology at time t • Computed as the solution to a linear programming problem, with the model exhibiting constant returns to scale:

  16. Subject to Where: kis the set of countries (k*is a particular country whose efficiency is being measured) jis the set of outputs,his the set of inputs, zkis the weight of thekth country data; and is the efficiency index.

  17. Malmquist Index • Output-based Malmquist productivity change index

  18. Malmquist Index • Allows for inefficient performance • Does not assume an underlying form for technology • Constructs a “world” frontier and compares each country to this frontier. • Two components: Efficiency change and technical change • The product of these two components yields a frontier version of productivity change

  19. Technical Change and Efficiency Change y2 Bt+1 Technical Change “Innovation” Bt At+1 g Efficiency Change “Catching-up” At St St+1 y1 O

  20. Efficiency and Technical Change

  21. y2 E K F g G C L D h H P(x) i y1 O j Distance Functions with multiple outputs

  22. Directional Distance Function • Nin et al. (2003): Input allocation • Specific input constraints for allocated inputs • Modified the directional distance function measure (Chung et al., 1997) • Defined as the contraction of inputs and the expansion of outputs (-gxgy) • One output: g = (yi, 0) • The distance function D(x, y; g = (yi, 0)) is the optimal objective value for the following problem:

  23. Subject to: A is the set of allocatable inputs, is the level of the allocatable input h used to produce output j of firm k, i is the particular output for which efficiency is being measured for firm k*, and index the other outputs (for which efficiency is not being measured).

  24. Directional Malmquist Index • Directional Malmquist Index for a specific Product/Sector (Nin-Pratt et al., 2003)

  25. Directional Malmquist Index • Efficiency and Technological Change Components:

  26. Limitations • Malmquist index may not be well defined • Reallocation factor bias in the measure • Movement of unallocated inputs from one activity to the other rather than technical growth. • Data • Which factors are relevant • Which peers (countries) to include • Zero output in some cases (i.e. pork production) • Other problems (not exclusive of Malmquist Index) • Which measures/indicators are appropriate?

  27. III. Productivity in Agriculture - Worldwide results and focus on Latin America Ludena et al., 2007. Productivity growth and convergence in crop, ruminant, and non ruminant production: measurement and forecasts. Agricultural Economics 37 (1): 1–17

  28. Empirical Application for Latin America • FAOSTAT: 116 countries, 1961-2001 • Outputs – Crops, Ruminants and Non Ruminants • Inputs • Land (Pastures, Arable and Permanent Crops) • Machinery (tractors, milking machines) • Animal Stock • Animal Feed • Fertilizers • Labor (in agriculture)

  29. Input-Output Allocation

  30. TFP in Agriculture (1961-2001) Annual Productivity Growth (%) in Agriculture and Subsectors

  31. IV. Productivity Growth in Latin America

  32. TFP in Agriculture in Latin America and the Caribbean Annual Productivity Growth (%) in Agriculture and Subsectors (1961-2001)

  33. Cumulative Productivity Index for Latin America and the Caribbean (1961 = 100) Source: Ludena et al. 2007.

  34. TFP in Agriculture in Latin America and the Caribbean (1961-2000)

  35. Annual TFP Growth (1961-200)Countries with Land Abundance (Ha./PEA > 12)

  36. Annual TFP Growth (1961-200) Countries with Land Constraint (Ha./PEA < 12)

  37. Cumulative Productivity Index for USA (1961 = 100)

  38. Cumulative Index Relative to the US

  39. V. External Shocks and Economic Reforms: Impacts on Agricultural Productivity - The cases of Brazil and Cuba

  40. Brazil and its agricultural policy – 1943-1980s • The corner stone of Brazil’s agricultural policy since 1943 until the mid 1980s was the Minimum Price Program (PPM). • Objective of the PPM: Reduce price risks and variability, hence promote more investment and agricultural production. • However, the PPM changed into a consumer subsidy program – “cheap food policy”. • Price control on more than 40 agricultural products, by fixing prices, controlling marketing margins and allowing subsidized imports to compete with domestic production.

  41. Brazil: Annual Productivity Growth in Agriculture (%)

  42. Brazil and the effect of economic reforms

  43. Brazil and its agricultural policy – 1985-2000 • In 1985 agricultural policies changed. • Trade liberalization and reduction of government intervention. • Deregulation and elimination of direct price controls in agricultural products. • This changes reduced costs and increased agricultural productivity.

  44. Brazil and its agricultural policy – 1985-2000 • Agricultural productivity grew at an annual rate of 3.26%. • Livestock sector grew the most: • Productivity growth in pigs and poultry grew at 10% per year. • Productivity in bovine meat and milk production grew at 5% per year.

  45. Brazil and its agricultural policy – 1985-2000 • More productivity in pigs and poultry due to reduced costs. • Incentives to move to corn and soybean production areas. • This has reduced feed costs, which are >50% of all costs in pigs and poultry production.

More Related