In his seminal work, Fontela (1989) set up the distributional rule of productivity gain in the input–output context (total factor productivity surplus, TFPS). Garau (1996) proposed an extension, to identify a measure of surplus, called purchasing power transfer (PPT). This measure is given by the productivity gains and market surplus generated by the extra-profit conditions derived from the rental positions detained by agents. Such a decomposition is useful because it provides information about the degree of non–competitiveness in different markets. In this paper, we compute and explain Fontela's (1989) TFPS by comparing it with Garau's (1996) PPT for Italy over 2009–2014.
Citation: Giorgio Garau. Total factor productivity and relative prices: the case of Italy[J]. National Accounting Review, 2022, 4(1): 16-37. doi: 10.3934/NAR.2022002
| [1] | Huiying Zhang, Jiayan Lin, Lan Zhou, Jiahui Shen, Wenshun Sheng . Facial age recognition based on deep manifold learning. Mathematical Biosciences and Engineering, 2024, 21(3): 4485-4500. doi: 10.3934/mbe.2024198 |
| [2] | Mubashir Ahmad, Saira, Omar Alfandi, Asad Masood Khattak, Syed Furqan Qadri, Iftikhar Ahmed Saeed, Salabat Khan, Bashir Hayat, Arshad Ahmad . Correction: Facial expression recognition using lightweight deep learning modeling. Mathematical Biosciences and Engineering, 2023, 20(6): 10675-10677. doi: 10.3934/mbe.2023472 |
| [3] | R Nandhini Abiram, P M Durai Raj Vincent . Identity preserving multi-pose facial expression recognition using fine tuned VGG on the latent space vector of generative adversarial network. Mathematical Biosciences and Engineering, 2021, 18(4): 3699-3717. doi: 10.3934/mbe.2021186 |
| [4] | Basem Assiri, Mohammad Alamgir Hossain . Face emotion recognition based on infrared thermal imagery by applying machine learning and parallelism. Mathematical Biosciences and Engineering, 2023, 20(1): 913-929. doi: 10.3934/mbe.2023042 |
| [5] | Jia-Gang Qiu, Yi Li, Hao-Qi Liu, Shuang Lin, Lei Pang, Gang Sun, Ying-Zhe Song . Research on motion recognition based on multi-dimensional sensing data and deep learning algorithms. Mathematical Biosciences and Engineering, 2023, 20(8): 14578-14595. doi: 10.3934/mbe.2023652 |
| [6] | Shuai Cao, Biao Song . Visual attentional-driven deep learning method for flower recognition. Mathematical Biosciences and Engineering, 2021, 18(3): 1981-1991. doi: 10.3934/mbe.2021103 |
| [7] | Yuanyao Lu, Kexin Li . Research on lip recognition algorithm based on MobileNet + attention-GRU. Mathematical Biosciences and Engineering, 2022, 19(12): 13526-13540. doi: 10.3934/mbe.2022631 |
| [8] | C Willson Joseph, G. Jaspher Willsie Kathrine, Shanmuganathan Vimal, S Sumathi., Danilo Pelusi, Xiomara Patricia Blanco Valencia, Elena Verdú . Improved optimizer with deep learning model for emotion detection and classification. Mathematical Biosciences and Engineering, 2024, 21(7): 6631-6657. doi: 10.3934/mbe.2024290 |
| [9] | Yufeng Qian . Exploration of machine algorithms based on deep learning model and feature extraction. Mathematical Biosciences and Engineering, 2021, 18(6): 7602-7618. doi: 10.3934/mbe.2021376 |
| [10] | Chelsea Harris, Uchenna Okorie, Sokratis Makrogiannis . Spatially localized sparse approximations of deep features for breast mass characterization. Mathematical Biosciences and Engineering, 2023, 20(9): 15859-15882. doi: 10.3934/mbe.2023706 |
In his seminal work, Fontela (1989) set up the distributional rule of productivity gain in the input–output context (total factor productivity surplus, TFPS). Garau (1996) proposed an extension, to identify a measure of surplus, called purchasing power transfer (PPT). This measure is given by the productivity gains and market surplus generated by the extra-profit conditions derived from the rental positions detained by agents. Such a decomposition is useful because it provides information about the degree of non–competitiveness in different markets. In this paper, we compute and explain Fontela's (1989) TFPS by comparing it with Garau's (1996) PPT for Italy over 2009–2014.
| [1] |
Antille G, Fontela E (2003) The terms of trade and the international transfers of productivity gains. Econ Syst Res 15: 3–19. https://doi.org/10.1080/0953531032000056918 doi: 10.1080/0953531032000056918
|
| [2] |
Babeau A (1978) The Application of the Constant Price Method for Evaluating the Transfer Related to Inflation: the Case of French Households. Rev Income Wealth 24: 391–414. https://doi.org/10.1111/j.1475-4991.1978.tb00066.x doi: 10.1111/j.1475-4991.1978.tb00066.x
|
| [3] | Baumol WJ (1967) Macroeconomics of unbalanced growth: the anatomy of urban crisis. Am Econ Rev 57: 415–426. https://www.jstor.org/stable/1812111 |
| [4] |
Baumol WJ, Wolff EN (1984) On inter industry difference in absolute productivity. J Political Econ 92: 1017–1034. https://doi.org/10.1086/261273 doi: 10.1086/261273
|
| [5] |
Carter AP (1990) Upstream and downstream benefits of innovation. Econ Syst Res 2: 241–257. https://doi.org/10.1080/09535319000000017 doi: 10.1080/09535319000000017
|
| [6] |
Flexner W (1959) An Analysis of the Nature of Aggregates at Constant Price. Rev Econ Stat 41: 400–404. https://doi.org/10.2307/1927267 doi: 10.2307/1927267
|
| [7] | Fontela E, Solari L, Duval A (1971) Production constraints and prices in an input-outptut system. Brody A., Carter A.P. (eds), Input-Output techniques, North Holland Publishing. |
| [8] |
Fontela E (1989) Industrial structure and economic growth: An input output perspective. Econ Sys Res 1: 45–52. https://doi.org/10.1080/09535318900000004 doi: 10.1080/09535318900000004
|
| [9] | Fontela E, Pulido AM (1993) Pasado, presente y futuro del analisis Input-Output. Econ Ind 290: 17–24. |
| [10] | Fontela E, Pulido AM (1993) Analisis input-output. Modelos, datos y aplicaciones, Editorial Piramide. |
| [11] |
Fontela E (1994) Inter-industry distribution of productivity gains. Econ SysT Res 6: 227–236. https://doi.org/10.1080/09535319400000020 doi: 10.1080/09535319400000020
|
| [12] | Fontela E, Lo Cascio M, Pulido A (2000) Systemic productivity and relative prices in an input-output framework. XIII International Conference on Input-Output Techniques, Macerata. |
| [13] | Fontela E (2002) Prix relative et structures de marches. Dialogue hors du temps avec Luigi Solari. Revue Europeenne des sciences sociales, 319–331. |
| [14] | Garau G (1996) La distribution des gains de la croissance: une analyse entrees sorties. ed. Lang, Berna. |
| [15] | Garau G (1997) Analisi spaziale dei trasferimenti di potere d'acquisto, Capitale Naturale e Ambiente, a cura di B. Moro, Franco Angeli, Milano. |
| [16] | Garau G (2002) Total factor productivity surplus in a SAM context. I International Conference on Economic and Social Statistics, China, Canton. |
| [17] | Garau G, Lecca P (2015) The impact of regional R and D subsidy in a computable general equilibrium model. Int Regional Sci Rev 38: 319–357. |
| [18] |
He M, Walheer B (2020) Technology intensity and ownership in the Chinese manufacturing industry: A labor productivity decomposition approach. Natl Account Rev 2: 110–137. https://doi.org/10.3934/NAR.2020007 doi: 10.3934/NAR.2020007
|
| [19] | Lo Cascio M, Carbonaro I, Guidi A (1998) Costruzione di un conto satellite dei trasporti: quadro di riferimento e problemi. Scritti di Statistica Economica 4, a cura di R. Guarini. |
| [20] | Masse P, Bernard P (1969) Les dividends du progrés. ed. du Seuil, Paris. |
| [21] | Mazzucato M (2014) Lo stato innovatore, ed. Laterza, Bari. |
| [22] | Piketty T (2014) Il capitale nel XXI secolo, ed. Bompiani, Milano. |
| [23] |
Rampa G (2008) Using weighted least squares to deflate input output tables. Econ Syst Res 40: 259–276. https://doi.org/10.1080/09535310802344349 doi: 10.1080/09535310802344349
|
| [24] | Rifkin J (2014) La società a costo marginale zero, ed. Mondadori, Milano. |
| [25] | Van Meijl H (1997) Measuring Intersectoral Spillover. Econ Syst Res 9. |
| 1. | Jassim AlMulla, Mohammad Tariqul Islam, Hamada R. H. Al-Absi, Tanvir Alam, Rahul Gomes, SoccerNet: A Gated Recurrent Unit-based model to predict soccer match winners, 2023, 18, 1932-6203, e0288933, 10.1371/journal.pone.0288933 | |
| 2. | Chaolin Tang, Dong Zhang, Qichuan Tian, Convolutional Neural Network–Bidirectional Gated Recurrent Unit Facial Expression Recognition Method Fused with Attention Mechanism, 2023, 13, 2076-3417, 12418, 10.3390/app132212418 | |
| 3. | Edy Winarno, Anindita Septiarini, Wiwien Hadikurniawati, Hamdani Hamdani, The Hybrid Features and Supervised Learning for Batik Pattern Classification, 2024, 17, 1556-4673, 1, 10.1145/3631131 | |
| 4. | Samla Salim, R. Sarath, BREAST CANCER DETECTION AND CLASSIFICATION USING HISTOPATHOLOGICAL IMAGES BASED ON OPTIMIZATION-ENABLED DEEP LEARNING, 2024, 36, 1016-2372, 10.4015/S101623722350028X | |
| 5. | Shengfu Zhang, Zhongjie Xiao, Facial Expression Recognition Using a Semantic-Based Bottleneck Attention Module, 2024, 20, 1552-6283, 1, 10.4018/IJSWIS.352418 | |
| 6. | Haoyu Zhou, Lingfeng Sang, Jingjing Luo, Hongbo Wang, Yongfei Feng, Xueze Zhang, Li Chen, Development of a multifunctional nursing bed system for in-bed position recognition and automatic repositioning, 2024, 238, 0954-4062, 5437, 10.1177/09544062231223878 | |
| 7. | Fen Wang, Kim Ju Kyoung, Leather Defect Detection Method in Clothing Design Based on TDENet, 2023, 11, 2169-3536, 104890, 10.1109/ACCESS.2023.3308493 | |
| 8. | A Çelik, E Tekin, Classification of Hatchery Eggs Using a Machine Learning Algorithm Based on Image Processing Methods: A Comparative Study, 2024, 26, 1806-9061, 10.1590/1806-9061-2023-1882 | |
| 9. | Jian‐Ting Shi, Gui‐Xu Qu, Zhi‐Jun Li, UCSwin‐UNet model for medical image segmentation based on cardiac haemangioma, 2024, 18, 1751-9659, 3302, 10.1049/ipr2.13175 | |
| 10. | P Karthikeyan, Kirutheesvar S, Sivakumar S, 2024, Facial Emotion Recognition for Enhanced Human-Computer Interaction using Deep Learning and Temporal Modeling with BiLSTM, 979-8-3315-0440-3, 1791, 10.1109/ICOSEC61587.2024.10722687 | |
| 11. | Muhammad Hameed Siddiqi, Irshad Ahmad, Yousef Alhwaiti, Faheem Khan, Facial Expression Recognition for Healthcare Monitoring Systems Using Neural Random Forest, 2025, 29, 2168-2194, 30, 10.1109/JBHI.2024.3482450 | |
| 12. | Kun Zheng, Li Tian, Jinling Cui, Junhua Liu, Hui Li, Jing Zhou, Junjie Zhang, An Adaptive Thresholding Method for Facial Skin Detection in HSV Color Space, 2025, 25, 1530-437X, 3098, 10.1109/JSEN.2024.3506579 | |
| 13. | Muhammed Telceken, Devrim Akgun, Sezgin Kacar, Kübra YESİN, Metin Yıldız, Can artificial intelligence understand our emotions? Deep learning applications with face recognition, 2025, 1046-1310, 10.1007/s12144-025-07375-0 |
Figures(6) / Tables(6)
Giorgio Garau. Total factor productivity and relative prices: the case of Italy[J]. National Accounting Review, 2022, 4(1): 16-37. doi: 10.3934/NAR.2022002
DownLoad: