| Literature DB >> 35270605 |
Yuhang Bai1, Li Li2, Fengting Wang2,3,4, Lizhong Zhang1, Lichun Xiong2,3,4.
Abstract
China's dairy product import volume and output continue to grow rapidly, and to a certain extent, it will form a substitute for the Chinese dairy market. Therefore, it is necessary to study the impact of the import of dairy products on the technological progress of raw milk production in China. Using the data from 2005 to 2017, this paper uses the DEA model and the input-output model to analyze the impact of China's dairy product imports on the technological progress of raw milk production. The model results show that: (1) there are differences in the technological content of dairy products from different importing countries; (2) The total technological content of imported dairy products hinders the improvement of the technological progress index of small, medium and large-scale production of raw milk in China, and has the most prominent negative impact on the technological progress of large-scale raw milk production in China; (3) The technological content of dairy products imports from New Zealand, Australia, Germany, the Netherlands and other countries can help improve the technological progress index of China's moderate-scale production of raw milk, while importing countries from the United States, Canada and other countries hinder it.Entities:
Keywords: DEA; dairy products import; production technological progress index; raw milk; technological content
Mesh:
Year: 2022 PMID: 35270605 PMCID: PMC8910074 DOI: 10.3390/ijerph19052911
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
The technical content of dairy products in China’s major import sources of dairy products.
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| 2005 | 746.205 | 42.615 | 8.404 | 1.486 | 0.878 | 9.693 | 0.384 |
| 2006 | 966.084 | 41.245 | 10.845 | 1.198 | 1.747 | 11.679 | 0.701 |
| 2007 | 812.595 | 54.112 | 11.242 | 1.554 | 14.668 | 17.669 | 1.323 |
| 2008 | 787.765 | 63.553 | 14.147 | 1.713 | 5.389 | 17.502 | 1.259 |
| 2009 | 1893.989 | 49.729 | 12.011 | 2.463 | 2.569 | 20.339 | 2.399 |
| 2010 | 3014.137 | 55.249 | 15.797 | 0.972 | 53.256 | 15.563 | 3.355 |
| 2011 | 2474.059 | 45.861 | 21.588 | 0.289 | 46.976 | 19.768 | 5.719 |
| 2012 | 3961.462 | 51.385 | 23.091 | 0.226 | 50.918 | 30.385 | 9.796 |
| 2013 | 5993.624 | 82.574 | 36.535 | 0.093 | 287.057 | 36.494 | 12.613 |
| 2014 | 7344.327 | 122.051 | 39.478 | 0.359 | 352.136 | 48.299 | 17.177 |
| 2015 | 4360.186 | 151.757 | 26.282 | 0.172 | 105.162 | 43.131 | 19.321 |
| 2016 | 5061.959 | 170.896 | 25.277 | 0.309 | 135.981 | 58.940 | 21.283 |
| 2017 | 6284.666 | 173.533 | 35.981 | 0.248 | 56.494 | 75.676 | 23.946 |
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| 2005 | 0.266 | 2.968 | 4.948 | 18.399 | 1.347 | 14.497 | 1.441 |
| 2006 | 0.107 | 4.541 | 4.459 | 18.069 | 0.645 | 13.754 | 2.809 |
| 2007 | 0.059 | 4.858 | 6.574 | 27.647 | 0.566 | 16.633 | 1.576 |
| 2008 | 0.015 | 3.271 | 7.552 | 18.886 | 1.067 | 17.233 | 0.452 |
| 2009 | 0.147 | 10.526 | 9.500 | 35.116 | 1.009 | 20.736 | 1.923 |
| 2010 | 1.046 | 38.035 | 8.190 | 31.913 | 3.177 | 20.800 | 3.595 |
| 2011 | 1.648 | 28.609 | 12.901 | 37.326 | 1.921 | 34.372 | 5.867 |
| 2012 | 1.344 | 23.355 | 14.324 | 63.680 | 3.559 | 39.148 | 5.116 |
| 2013 | 2.094 | 28.733 | 19.342 | 64.666 | 4.531 | 51.784 | 8.051 |
| 2014 | 4.725 | 44.311 | 18.281 | 73.860 | 5.631 | 55.643 | 15.755 |
| 2015 | 3.885 | 45.138 | 22.762 | 52.941 | 4.079 | 62.324 | 14.531 |
| 2016 | 6.198 | 43.538 | 25.629 | 52.934 | 5.511 | 52.144 | 12.440 |
| 2017 | 8.635 | 58.811 | 33.971 | 57.605 | 7.064 | 61.948 | 16.059 |
Data source: Uncomtrade website.
China’s raw milk production technology progress index from 2005 to 2017.
| Time | Small Scale | Medium Scale | Large Scale |
|---|---|---|---|
| 2005 | 1.026 | 0.956 | 1.043 |
| 2006 | 1.697 | 1.201 | 1.400 |
| 2007 | 0.803 | 0.677 | 0.532 |
| 2008 | 1.068 | 1.213 | 1.183 |
| 2009 | 1.013 | 1.208 | 1.125 |
| 2010 | 1.221 | 1.003 | 0.626 |
| 2011 | 0.829 | 1.069 | 1.335 |
| 2012 | 0.800 | 0.768 | 1.109 |
| 2013 | 1.408 | 1.182 | 0.960 |
| 2014 | 0.803 | 0.642 | 0.860 |
| 2015 | 1.011 | 1.360 | 1.677 |
| 2016 | 0.941 | 1.180 | 0.809 |
| 2017 | 1.035 | 0.937 | 0.690 |
| Mean Value | 1.050 | 1.030 | 1.027 |
Note: China’s raw milk production technology progress index is calculated according to the “National Agricultural Product Cost and Benefit Data Collection (2006–2018)”; The number of dairy cows determines the scale of raw milk production farms, Chinese scholars, Statistical yearbooks usually define 10–50 cows as small-scale raw milk production farms; 50–500 cows as medium-scale raw milk production farms; 500+ cows as large-scale raw milk production farm.
The influence of imported technology total content of dairy products on the technological progress index of the large-scale production of raw milk.
| Variable | Small-Scale Technological | Medium-Scale Technological | Large-Scale | |||
|---|---|---|---|---|---|---|
| Coef | SE | Coef | SE | Coef | SE | |
| etc | −0.005 * | 0.003 | −0.011 *** | 0.003 | −0.016 *** | 0.004 |
| city | −0.001 | 0.004 | 0.002 | 0.004 | −0.403 | 0.527 |
| rural | 0.311 | 0.24 | 0.402 ** | 0.189 | 0.19 | 0.245 |
| profit | 0.134 | 0.122 | 0.184 * | 0.095 | 0.076 | 0.13 |
| policy | −0.094 | 0.067 | 0.214 *** | 0.07 | 0.274 *** | 0.096 |
| cons | 1.01 *** | 0.197 | 0.927 *** | 0.154 | 1.551 *** | 0.397 |
| F | 16.7 *** | 17.95 *** | 13.97 ** | |||
| Observations | 169 | 247 | 247 | |||
Note: coef is the coefficient of each variable; SE is the standard deviation; cons is a constant term; ***, **, * indicate significance at the 1%, 5%, and 10% significance level, respectively. Source: Uncomtrade, “China Dairy Industry Yearbook”, “Compilation of National Agricultural Product Production Income Data”.
Influence of technology content of import source country on technological progress of raw milk production.
| Country | Techch | Techch | |||||
|---|---|---|---|---|---|---|---|
| Import Source Country | Coef | SE |
| Import Source Country | Coef | SE |
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| New Zealand | 1.248 | 0.127 | 0.000 | Australia | 0.415 | 0.095 | 0.000 |
| USA | −1.122 | 0.157 | 0.000 | Canada | −0.123 | 0.043 | 0.005 |
| Uruguay | −0.033 | 0.027 | 0.220 | France | / | / | / |
| German | 0.427 | 0.111 | 0.000 | UK | −0.081 | 0.031 | 0.009 |
| Denmark | −0.451 | 0.102 | 0.000 | The Netherlands | 0.944 | 0.139 | 0.000 |
| Finland | −0.639 | 0.125 | 0.000 | Belgium | −0.328 | 0.052 | 0.000 |
| Irish | / | / | / | Poland | / | / | / |
| city | −0.0001 | 0.002 | 0.951 | rural | 0.079 | 0.123 | 0.518 |
| profit | 0.077 | 0.061 | 0.208 | policy | / | / | / |
| cons | −2.01 | 0.758 | 0.000 | ||||
Note: coef is the coefficient, SE is the standard deviation, p is the significance, and cons is the constant term.