F. Hasanov, Elchin Suleymanov, H. Aliyeva, Hezi Eynalov, Sa’d Shannak
{"title":"是什么推动了阿塞拜疆的农业增长?来自超饱和自动计量学的见解","authors":"F. Hasanov, Elchin Suleymanov, H. Aliyeva, Hezi Eynalov, Sa’d Shannak","doi":"10.11118/actaun.2022.012","DOIUrl":null,"url":null,"abstract":"The development of the agricultural sector is essential for any economy, including Azerbaijan, the largest economy in the South Caucasus, as it plays an important role in food security, rural development, and environmental protection. For Azerbaijan, as an oil-dependent economy, it is also important for diversification of the non-oil sector. For this reason, the Azerbaijani government has adopted several programs and materialized massive investments to promote agricultural growth. This study examines the role of the production factors in the development of the sector using annual time series data for the period 1995–2017. Econometric analysis, mainly Autometrics - a cutting edge machine learning modeling algorithm- with super saturation, and Growth Accounting lead us to conclude that: (i) land, labor, and capital have statistically significant positive long-run impacts on agriculture output; (ii) the growth of the sector and the contributions of land and capital formation slowed down sharply, while the contributions of total factor productivity (TFP) and labor increased in 2009–2017 compared to the pre-2009 period; (iii) in the pre-2009 period, the sector's growth was hugely contributed by capital followed by TFP, labor and land; (iv) in 2009–2017 period, TFP followed by capital and labor contributed to the sector's growth, while the contribution of land was negative. The results are robust to different econometric methods and specifications. Overall, policymakers are recommended to consider that value-added and other key indicators of agriculture have grown less in 2009–2017 period compared to the pre-2009 period, given that one should expect more growth in the former period as numerous government programs and massive investments were materialized. They may also consider that the contributions of labor and land were quite small and negative, respectively. Lastly, policies leading to TFP growth should be supported.","PeriodicalId":7174,"journal":{"name":"Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis","volume":"13 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"What Drives the Agricultural Growth in Azerbaijan? Insights from Autometrics with Super Saturation\",\"authors\":\"F. Hasanov, Elchin Suleymanov, H. Aliyeva, Hezi Eynalov, Sa’d Shannak\",\"doi\":\"10.11118/actaun.2022.012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The development of the agricultural sector is essential for any economy, including Azerbaijan, the largest economy in the South Caucasus, as it plays an important role in food security, rural development, and environmental protection. For Azerbaijan, as an oil-dependent economy, it is also important for diversification of the non-oil sector. For this reason, the Azerbaijani government has adopted several programs and materialized massive investments to promote agricultural growth. This study examines the role of the production factors in the development of the sector using annual time series data for the period 1995–2017. Econometric analysis, mainly Autometrics - a cutting edge machine learning modeling algorithm- with super saturation, and Growth Accounting lead us to conclude that: (i) land, labor, and capital have statistically significant positive long-run impacts on agriculture output; (ii) the growth of the sector and the contributions of land and capital formation slowed down sharply, while the contributions of total factor productivity (TFP) and labor increased in 2009–2017 compared to the pre-2009 period; (iii) in the pre-2009 period, the sector's growth was hugely contributed by capital followed by TFP, labor and land; (iv) in 2009–2017 period, TFP followed by capital and labor contributed to the sector's growth, while the contribution of land was negative. The results are robust to different econometric methods and specifications. Overall, policymakers are recommended to consider that value-added and other key indicators of agriculture have grown less in 2009–2017 period compared to the pre-2009 period, given that one should expect more growth in the former period as numerous government programs and massive investments were materialized. They may also consider that the contributions of labor and land were quite small and negative, respectively. 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What Drives the Agricultural Growth in Azerbaijan? Insights from Autometrics with Super Saturation
The development of the agricultural sector is essential for any economy, including Azerbaijan, the largest economy in the South Caucasus, as it plays an important role in food security, rural development, and environmental protection. For Azerbaijan, as an oil-dependent economy, it is also important for diversification of the non-oil sector. For this reason, the Azerbaijani government has adopted several programs and materialized massive investments to promote agricultural growth. This study examines the role of the production factors in the development of the sector using annual time series data for the period 1995–2017. Econometric analysis, mainly Autometrics - a cutting edge machine learning modeling algorithm- with super saturation, and Growth Accounting lead us to conclude that: (i) land, labor, and capital have statistically significant positive long-run impacts on agriculture output; (ii) the growth of the sector and the contributions of land and capital formation slowed down sharply, while the contributions of total factor productivity (TFP) and labor increased in 2009–2017 compared to the pre-2009 period; (iii) in the pre-2009 period, the sector's growth was hugely contributed by capital followed by TFP, labor and land; (iv) in 2009–2017 period, TFP followed by capital and labor contributed to the sector's growth, while the contribution of land was negative. The results are robust to different econometric methods and specifications. Overall, policymakers are recommended to consider that value-added and other key indicators of agriculture have grown less in 2009–2017 period compared to the pre-2009 period, given that one should expect more growth in the former period as numerous government programs and massive investments were materialized. They may also consider that the contributions of labor and land were quite small and negative, respectively. Lastly, policies leading to TFP growth should be supported.