1 / 53

SEBA Beijing Normal University Email: yheng@bnu

Searching for the Robust Method to Estimate Total Factor Productivity at Firm Level Yin Heng Li Shigang Liu Di. SEBA Beijing Normal University Email: yheng@bnu.edu.cn. Motivation. Discuss the robust TFP estimation method at firm level, using competitive industry as an example.

adanne
Télécharger la présentation

SEBA Beijing Normal University Email: yheng@bnu

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. Searching for the Robust Method to Estimate Total Factor Productivityat Firm LevelYin Heng Li Shigang Liu Di SEBA Beijing Normal University Email: yheng@bnu.edu.cn

  2. Motivation • Discuss the robust TFP estimation method at firm level, using competitive industry as an example.

  3. What does TFP measure? • Evaluate the input-output efficiency • Labor productivity cannot describe the true efficiency at firm level • The core of TFP estimation is dealing with the substitution among input factors

  4. The importance of TFP estimation • Productivity is not everything, but approximates everything in the long run. Krugman（1997） • The factors affecting TFP • Is the TFP of firms improved? • Misallocation of resources - Can the economic environment promotes firms with high TFP, and suppress or expel those with low TFP?

  5. The current situation of TFP estimation • Great differences exist even in researches appeared in the top journals - Young (1995)’s estimation of the growth rate of TFP in Hong Kong and Taiwan district in China is between 2% and 3%, the growth rate of Korea is 1.7% - Hsieh (1999) got 3% more than Young’s.

  6. Structure • The measurement of data and variables • Traditional methods • Firms’ decision and structure estimation • Value-added or gross output production function • Sample selection, function form and other robust test • summary

  7. The measurement of data and variables • Panel construction • Goal : identify firms across years • Problems : • Different firms may share the same code • Firms may change the code because of changing name or structure etc. • Idea : • Make sure that firms with the same code is the same one; • Match firms with the combination of relatively stable information, such as name, head, telephone, etc.; • Correct the wrong matching.

  8. The measurement of data and variables • The measurement of output • The real output • deflate gross output from three dimensions: time(year), space(province), industry(two-digit) • The measurement of input • Construct the input deflator from time(year), space(province) and industry(two-digit), based on input-output table, like Brandt (2012).

  9. The measurement of data and variables • The measurement of capital • Estimate nominal investment from the found year with the data of original fixed capital • Deflate the nominal investment to get the real investment • Get the real capital with perpetual inventory method • The measurement of labor • Total average number of staff

  10. The measurement of data and variables • The choice of industries • Two-digit industry 18: manufacture of clothing, shoes and hats; two-digit industry 19: manufacture of leather, fur and feather • Data clearing • Delete the sample with non-positive output, capital, labor and input • Delete the sample with less than 8 workers • Delete the sample with bigger value-added than output

  11. Traditional methods • DEA (Data Envelopment Analysis) • Index method • Tradition parametric methods • OLS • FE • BB

  12. Traditional methods • DEA • Considering the heterogeneity of firms’ TFP • Get the TFP measurement from the input and output data with linear programming, treating the production process as a black box • It is a determinate method which can be sensitive to the random error or extreme values.

  13. Traditional methods • Index method • Free of function form • Need the given the parameter of return to scale • Without the consideration of random error • Based on the hypothesis that all inputs are static input without adjustment cost

  14. Traditional methods • Parametric method • Based on the set that all firms in the same industries have the same elasticity of output of capital, labor and input • Deal with random error

  15. Traditional methods • OLS • Endogenous problem • FE • Neglect the change of TFP with time • AB/BB • ， • System GMM

  16. Firms’ decision and structure estimation • The more information of firm’s action and decision we use, the more robust and accurate result we can get. • Tradition methods neglect the information of firm’s action and decision structure.

  17. Firms’ decision and structure estimation • Data generating process at firm level • Firms choose input and output to maximize the profit based on the observed productivity • Where is planed output, the real output is

  18. Firms’ decision and structure estimation • The decision structure of firm’s factor input: dynamic and static • Two adjustment frictions make the firm’s input decision dynamic: • Adjustment cost, such as the cost of installment, test and dismantle • Adjustment lag, because the factor used now is decided at the former period

  19. Firms’ decision and structure estimation • The decision structure of firm’s dynamic input: take capital as an example

  20. Firms’ decision and structure estimation • The decision structure of firm’s static input : materials

  21. Firms’ decision and structure estimation • The decision structure of firm’s labor input ( may change with industry) • Treated as dynamic if the adjustment cost cannot be neglected • Adjustment cost : training cost when employing new staff and the cost of layoff • Adjustment lag : new staff can only get to work after the training • Treated as static if the adjustment cost can be neglected

  22. Firms’ decision and structure estimation • Model • C-D production function • Hicks-neutral techniques • Static labor input

  23. Firms’ decision and structure estimation • Olley & Pakes（1996） • Get productivity from the investment function , and then take it into the production function • Step 1. get with nonparametric method, and then the productivity can be expressed as =； • Step 2. let productivity follows the Markov process,get the estimation of with the moment condition

  24. Firms’ decision and structure estimation • Levinsohn & Petrin (2003) • A great loss of investment information • Use materials as proxy variables:

  25. Firms’ decision and structure estimation • Bond & Söderbom (2005)and Ackerberg et al.(2006): Collinearity problem • Robinson (1988): “The variables in the parametric part cannot be predicted by those in the nonparametric part in the sense of OLS.” • Newey et al.(1999): There should exist no function between parametric part and nonparametric part in semi-parametric model.

  26. Firms’ decision and structure estimation • Ackerberg et al.(2006) • Capital is decided before TFP • Labor decision is before materials

  27. Firms’ decision and structure estimation • Step 1. the production function is , get 、with nonparametric method, and the productivity is • Step 2.the productivity follows Markov process, get the other parameters with the moment condition

  28. Firms’ decision and structure estimation • The idea of the new structural estimation of TFP at firm level • Review the index method about estimating static input • Solow(1957)； • Caves et al.(1982)； • Hall(1989) • Separate the estimation of static input and dynamic input • Gandhi et al.(2011)

  29. Firms’ decision and structure estimation • new structural estimation of TFP • Get the following formula according to the optimal condition of static input • the Hicks-neutral technique allows Where is the share of materials to nominal output • Get 、、with nonparametric regression, and in the situation of C-D production function, the mean of is

  30. Firms’ decision and structure estimation • If labor is static input, then get with the method above, if not, get the estimation of at the next step • The productivity follows Markov process same as OP/LP/ACF, and get with the moment condition

  31. Firms’ decision and structure estimation • New structural estimation of TFP • Step 1. estimate the parameter of static input following the idea of index method • Step 2. estimate the parameter of dynamic input following the idea of structural estimation • The advantages • Avoid the assumptions in the proxy variables method such as the reversible proxy function and the measurement error • Make full use of firms’ decision • Solve the endogenous problem and the collinearity problem

  32. Gross output or Value-added? • Gross output (sales) is the real observable variable by firms who experience the production and management process, while value-added is just a statistical concept.

  33. Gross output or Value-added? • Value-added can be proper only if the theoretic definition is agreed with empirical measurement, which needs the following assumptions Assumption 1. Labor and capital produce value-added following , and combine with materials according to to form output

  34. Gross output or Value-added? • The core in TFP estimation is to control the substitution among factors • Make the following choices to maximize profit • Labor intensive • Capital intensive • Outsource and material intensive • Value-added production function only consider the substitution between labor and capital and neglect the efficiency from materials

  35. Gross output or Value-added?

  36. Gross output or Value-added? • The result misusing value-added • New endogenous problem appears because is put into the error term • TFP heterogeneity will be exaggerated because the heterogeneity coming from materials is put into TFP difference

  37. Sample selection, function form and other robust test • Sample selection problem • There is a great number of entry and exit in the data, and we can only observe the existed ones • The structure estimation method don’t have to deal with sample selection problem because of the proxy of in the first step

  38. Sample selection, function form and other robust test • We can only observe the existed samples with, and ,so there is endogenous problem in the second step • How to deal with it? • Rules of entry and exit： • Conditional expectation：

  39. Sample selection, function form and other robust test • The probability that a firm i stay in period t • Get • Put into the conditional expectation of productivity

  40. Sample selection, function form and other robust test • Trans-log production function • Cobb-Douglas production function is a special situation of trans-log production function.

  41. Summary • The problems of tradition methods • DEA method tries to measure TFP by construct a set of substitution of factors by linear programming, but determinate method cannot get the robust estimation with the data at firm level, because the measurement error cannot be neglected.

  42. Summary • Index method is also not satisfactory because all the inputs are assumed to be static and the parameter of return to scale should be given. • Traditional methods, such asFE,IV and dynamic panel, will not get the robust result because the disturbance should be given before the estimation.

  43. Summary • Structural estimation method, which is becoming the most potential approach, tries to open the black box of the firms’ production process by making full use of the information of their behavior and decision-making. • Olley and Pakes (1996), Levinsohn and Petrin (2003),Ackerberg et al.(2006) all face the “collineraity” problem. • The new structural estimation, which combines the structural estimation with the traditional index method, may get the most robust estimation of TFP at firm level.

  44. Summary • The definition of variables affects the robustness of TFP estimation -measuring firms’ output with value-added will exaggerate TFP heterogeneity seriously • Sample selection and the production function form also affect the TFP estimation

More Related