A Retake on Productivity Growht, Technical Progress and Efficiency Change using Malmquist Productivity Indexes.
Bibliographic record
Abstract
This thesis follows methods employed by Färe et al. (1994) in their influential article ‘Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries’, published in the American Economic Review. The study is conducted using measures of output-oriented gross domestic product, the number of people working and the capital stock for 17 OECD countries from Penn World Tables (PWT), version 8.0, for 2002 to 2011. This retake use the same countries and the same data source as Färe et al. (1994) albeit their data was from the PWT, Mark 5 from 1991.\nProductivity is defined as a ratio of outputs and inputs and this particular productivity analysis is performed using an output-oriented Malmquist productivity change index, an index that can be decomposed into technological change and efficiency change components. This is done using data envelopment analysis techniques meaning that a technological frontier is constructed using non-parametric linear programming given assumption of the returns to scale characteristics. The frontier is the efficient frontier that all data points are evaluated against using distance functions. In total, 612 linear programming problems need be computed per data set for which the mathematical programming software MATLAB was used. The methods were first tested on PWT data set that Färe et al. (1994) used. To yield the expected results, the returns to scale assumption had to be changed from constant returns to scale (CRS) to non-increasing returns to scale (NIRS). This is in contrast to the explicit description from Färe et al. (1994) which state CRS as the results clearly reveal that NIRS must have been used.\nThe same methods and assumptions were then used for the PWT version 8.0 data set. The results differed from those of Färe et al. (1994) with regards to which countries that established the frontier while the rate of productivity growth had slowed down. Depending on scale assumption, the determining countries were Ireland, Norway, Sweden and the United States under NIRS or Ireland and Sweden for CRS. Regardless of scale assumption, Sweden was the sole determinant of the frontier for the last year of 2011. Just as the 1994 results by Färe et al. (1994), productivity growth was driven by technological improvements rather than efficiency gains. Sweden was notably the worst performing country with respect to technology and the best performer regarding efficiency. Norway was the best performer with regards to overall productivity growth due to good results for both of the subcomponents.\nFinally, the same techniques were applied to PWT 8.0 data for the same time period and countries as in the 1994 study and the results were significantly different. Canada, Ireland, Norway and the United States determined the frontier using NIRS meanwhile only Canada and Ireland were on the frontier given CRS. The overall productivity growth was slightly lower at 0.61 instead of 0.7 percent annually. That technological improvements were the main productivity driver, a conclusion by Färe et al. (1994), was reversed and Japan went from the best performing country to the fourth. Several countries shifted places and the discrepancies between the results for PWT Mark 5 and PWT 8.0 were wide-spread and vast.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".