Total Factor Productivity Index Research Articles

The effect of COVID-19 pandemic on the efficiency of training and research hospitals in Turkey

The Coronavirus disease 2019 (COVID-19), which emerged in December 2019, caused an increase in the demand for healthcare services globally. Hospitals’ operational and financial performances are thought to have been negatively affected by COVID-19 because they had to postpone providing non-urgent healthcare services to prevent infection. This study aimed to evaluate how the COVID-19 pandemic has affected the efficiency of training and research hospitals in Turkey. The study population comprised 51 training and research hospitals. The Malmquist Total Factor Productivity index was used to examine the changes in the efficiency of the training and research hospitals between 2017–2018, 2018–2019, 2019–2020, and 2020–2021. In addition, a repeated-measures ANOVA test was used to evaluate whether a significant difference existed in the efficiency levels of the hospitals in the pre-COVID-19 pandemic periods (2017–2018 and 2018–2019) and during them (2019–2020 and 2020–2021). No significant difference was found between hospitals' technical and scale efficiency levels before and during the pandemic, but the change in total factor productivity was significant (F = 34.18; p < 0.001). Our research findings provide clues about how hospitals' behaviours changed during the pandemic compared to before the pandemic. It was observed that efficiency decreases in hospitals at the onset of the pandemic disappeared with the adaptation process to the new normal. Technical efficiency decreased in two periods (2017–2018 and 2020–2021) when total factor productivity increased. Reverse changes in total factor productivity and technical efficiency indicate that technological change drives total factor productivity. This study identified differences in hospital efficiency during both ordinary and extraordinary periods. It would benefit managers and policymakers to recognise these differences and focus on managerial skills that ensure technical efficiency in extraordinary circumstances to mitigate possible efficiency losses.

Estimating the productivity of US agriculture: The Fisher total factor productivity index for time series data with unknown prices

AbstractIn this paper, we propose a straightforward way to estimate the Fisher ideal total factor productivity (TFP) index (FI) in cases where price information is unavailable, using ‘shadow prices’ derived from data envelopment analysis (DEA). A Monte Carlo experiment shows that the shadow price Fisher ideal TFP index (SPFI) can effectively estimate the ‘true’ FI with relatively small (and stable) errors. The empirical application to the US agriculture sector (1948–2017) further suggests that the SPFI is a (superior) alternative to the traditional Malmquist DEA, especially in dealing with unbalanced panel or time series data when price data are unknown.

Measuring the productivity of urban commercial banks in China

This paper contributes to the productivity analysis literature by measuring the productivity of 76 urban commercial banks operating in China's 27 regions from 2013 to 2018. A spatial total factor productivity index is constructed using a spatial autoregressive production function. The index is decomposed into the efficiency change and the returns to scale change, and it identifies both spatial direct (feedback) and spatial indirect (spillovers) components. The result confirms positive spatial dependence in the production of urban commercial banks. Additionally, productivity of China's urban commercial banks increases, which is mainly contributed to by the returns to scale change.

Efficiency Analysis of Life Insurance Companies in Indonesia and Malaysia

This study focuses on measuring the performance of life insurance companies in Indonesia and Malaysia. Input oriented Data Envelopment Analysis (DEA) uses panel data to extract the efficiency score of 5 life insurance companies from Indonesia and 5 life insurance companies from Malaysia for the year of 2015-2019. DEA-based Malmquist Total Factor Productivity (TFP) Index used to measure the efficiency change along the study period. This study utilizes asset and operating expenses as input variables, as for output variables, this study utilizes premium and investment income. Based on an efficiency score computed by DEA, most of the life insurance companies in both countries perform efficiently during the study period. However, life insurance companies in Indonesia still perform more efficiently than Malaysian life insurance companies. The results of the Malmquist TFP Index for life insurance companies in both countries show that there is 2.5% improvement in technical efficiency change, 1.5% deterioration in technology efficiency change, 0.6% improvement in pure efficiency change, 1.9% improvement on scale efficiency change, and 0.9% increase in TFP change. It shows that the main reason for TFP increased is due to improvement of technical efficiency change.

Knowledge spillovers along the sustainable supply chain of China's listed companies: The role of long-term orientation

A new industrial development paradigm, the Fifth Industrial Revolution or ‘Industry 5.0’ is expected to humanise green technological innovation (GTI), social resilience, and sustainable development of industrial ecosystems. Emphasising the supplier-customer interaction, ‘Industry 5.0’ is technological revolution, which is a value-driven initiative that drives knowledge spillovers along the sustainable supply chain (SSC). In this context, enterprises are incorporating more GTI activities into their partners’ SSC strategies. This study employs samples of China's A-share listed companies covering the period from 2010 to 2021 to examine the spillover effects between customers’ GTI and suppliers total factor productivity (TFP). Both GTI and TFP indicators are important representations of ‘Industry 5.0’, with our major concerning on the enhancement of supplier's long-term orientation (LTO). We calculated TFP by the Olley-Pakes and Levinsohn-Petrin methods, dividing GTI indicators into three levels: substantial green technological innovation (SGTI), non-substantial green technological innovation (NGTI), and overall green technological innovation (OGTI). Our empirical results show that 1) Customer's GTI contributes to supplier's TFP, and supplier's LTO including environmental, social & governance (ESG) performance, and R&D input can strengthen this beneficial link; 2) customer's NGTI represents a significant differentiation in comparison with SGTI, where R&D investment weakens the positive relationship between customer's NGTI and supplier's TFP; 3) heterogeneity analysis indicates that the spillovers of customer's GTI on supplier's TFP are more pronounced among state-owned enterprises, high-tech enterprises, and non-polluting enterprises. Notably, the connectedness demonstrates dynamic patterns through 2SLS and GMM regressions, highlighting the importance of enterprises' SSC and LTO being the shock transmitters to their TFP. Our study is prone to benefit lawmakers, regulators, and firm executives responsible for analysing and assessing the SSC, providing more policy implications with future prospects for sustainable transformation in the upcoming ‘Industry 5.0’ era.

Production Performance and Profitability of Small-scale Commercial Poultry Farms in Arsi and East-Showa Zones, Central Ethiopia

Poultry farming and the demand for chicken meat and eggs are growing due to their quality protein, essential nutrients, affordable price, and low investment cost. The current study was designed to investigate the productivity and profitability of small-scale commercial poultry enterprises. Data were collected from 221 poultry farms using a semi-structured questionnaire. The results were presented using descriptive statistics. Farm performances were measured by total-factor-productivity (TFP), benefit-cost-ratio (BCR), and net-profit-margin (NPM). The majority of the poultry farm owners were male (69.68%) and married (77.4%). Around 55.2% of poultry farmers aged 31-45 years. Group-owned farms had 4.59 ± 1.77 individual members. On average, a batch of layer chickens was kept for 17.0 ± 3.87 and 18.12 ± 4.25 months on individual and group-owned farms, respectively. Moreover, the mean selling ages of pullet and broiler chickens were 2.55 ± 0.71 and 2.18 ± 0.51 months, respectively. The flock size of layer chickens in sole-proprietor farms (562 ± 724) was significantly lower than in partnership farms (1165 ± 877). The average numbers of produced pullets by sole-proprietorship and partnership farms were 3177 ± 2360 and 3137 ± 1826, while the mean numbers of broilers produced were 2257 ± 1875 and 3269 ± 1669, respectively. The average egg and broiler weights in sole-proprietorship farms were significantly higher compared to group-owned farms. Annual egg production rates in individual and group-owned farms were 76.5% and 70.4%, respectively. The cost of feed, chicken, housing, labor, and medication were the top five production expenditures, while feed cost shares 60.4%. Egg producers had NPM, BCR, and TFP indices of 38.99%, 1.03, and 2.03, respectively, with notable differences by ownership types. The NPM, BCR, and TFP indices for broiler and pullet farms, respectively, were 42.78%, 0.93, and 1.93 for broilers and 35.21%, 0.92, and 1.67 for pullets. The results indicated that poultry firms performed optimally, regardless of ownership type. To further improve the efficiency and profitability of poultry enterprises, farmers need technical, finance, and management skills and input supply chains. Keywords: Broiler, Layer, Poultry, Production, Profitability, Pullet

New evidence of the driving forces behind Brazil's agricultural TFP growth—A stochastic frontier analysis with climatic variables and land suitability index

AbstractUsing panel data from 510 Brazilian micro‐regions in three census years (1995, 2006 and 2017), this study presents a productivity decomposition for the Brazilian agricultural sector using stochastic production frontier methods that account for the effects of rainfall, temperature and the land suitability index. We also calculated the total factor productivity (TFP) index and decomposed it into technical efficiency, technological change, scale efficiency and environmental efficiency. This article thus provides a new and more realistic assessment of recent Brazilian agricultural productivity growth. In recent decades, Brazilian agriculture has become widely known for presenting fast productivity growth; however, our results suggest that a lower TFP growth rate than previous estimates (1.96% per annum) and the overall effects of climate change could potentially compromise Brazilian agricultural TFP growth in the long run. Our findings might thus generate insights for agricultural and regional policies to increase efficiency in the sector and promote sustainable agricultural development in Brazil, which will contribute to the sector's competitiveness in international markets, the country's social and economic welfare, and environmental conservancy.

Carbon emission efficiency of land use in urban agglomerations of Yangtze River Economic Belt, China: Based on three-stage SBM-DEA model

Exploring regional differences in land use carbon emission efficiency (LUCE) and the path of collaborative emission reduction in the Yangtze River Economic Belt (YREB) are of immense importance to achieve the sustainable regional development. Firstly, based on the estimation method of land use carbon emissions, this paper scientifically calculates the carbon emission of land use of the Yangtze River Delta urban agglomeration (YRD), the middle reaches of the Yangtze River urban agglomeration (MRYR), and the Chengdu-Chongqing urban agglomeration (CC) from 2010 to 2021 in the YREB. And the carbon emission of land use of each city in urban agglomerations was obtained, which was regarded as the unexpected output in the efficiency evaluation index system. Secondly, the three-stage SBM-DEA model was used to reveal the LUCE and its spatiotemporal characteristics in different regions from a static perspective. The empirical results of the second stage SFA showed that the level of economic development, urbanization rate, industrial structure, non-agricultural conversion rate of agricultural land, the level of scientific and technological innovation and government intervention had significant effects on LUCE. By comparing the efficiency values and their decompositions in the first and third stage of various urban agglomerations, it was found that after eliminating environmental and random factors, the average ranking of comprehensive technical efficiency (TE) of land use carbon emission changed from YRD > MRYR > CC to YRD > CC > MRYR due to the cross influence of pure technical efficiency (PTE) and scale efficiency (SE). Thirdly, Malmquist index model was used to analyze the change of total factor productivity index (TFPch) and its spatiotemporal pattern from a dynamic perspective. It was found that the TFPch, technological progress index (TC), pure technical efficiency index (PEC) and scale efficiency index (SEC) of land use carbon emission of the three major urban agglomerations all showed varying degrees of increase after adjustment. Finally, to further analyze the impact of technological progress, PTE and SE on LUCE, a regression model was constructed with LUCE of each city in urban agglomeration as the dependent variable, and TC, PEC and SEC as independent variables. It was concluded that technological progress was the main factor to promote the improvement of LUCE in the whole YREB. The trend of changes of LUCE in various urban agglomerations was closely related to its management level, technology level and factor structure adjustment. The above conclusions provide support for the coordinated emission reduction path of urban agglomerations in the YREB from the perspective of land use, which is conducive to actively and steadily promoting the realization of carbon peak and carbon neutrality goals.

The driving factors of spatial differences on the whole life cycle carbon emissions of the construction industry: from the analysis perspective of total factor productivity

The energy saving and emissions reduction of the construction industry are crucial for China to achieve the “carbon peaking and carbon neutrality” goals. In order to promote the green development of the life cycle of the construction industry and improve the efficiency of emissions reduction. This paper examines the spatial-temporal distribution of life cycle carbon emissions in China’s construction industry (LCCECI) from 2004 to 2018. It uses the SBM-Malmquist total factor productivity (TFP) index to measure technological progress and establishes the spatial econometric model based on the STIRPAT model. The study investigates the driving factors of the LCCECI at the provincial and regional levels, aiming to provide suggestions for low-carbon development in the construction industry. The research results are as follows. ① The growth in the SBM-Malmquist TFP index of the construction industry distinctly curbs the LCCECI. ② Total population and urbanization level are not the primary driving factors for the LCCECI. The growth of per capita GDP significantly induces the LCCECI, while concurrently exhibiting a notable inhibitory effect on the LCCECI of neighboring regions. ③ The improvement of the SBM-Malmquist TFP index is conducive to the reduction of the LCCECI in the three major regions. The per capita GDP has the largest positive driving effect of the LCCECI in the eastern region, and the urbanization level the urbanization rate only significantly inhibits the growth of the LCCECI in the central region.

An innovative approach to evaluating sustainable development performance: The case of Turkey

AbstractThe assessment of sustainable development necessitates precise productivity measurement. Existing literature reveals a wide array of methods employed for this purpose. However, these approaches give rise to concerns regarding the accurate assessment of both efficiency (EC) and technical (TC) changes. Additionally, the data used for productivity measurement are often subject to uncertainty. In response to these shortcomings in the existing literature, this study introduces the Environmental Fuzzy Malmquist Total Factor Productivity (EFM) index for productivity measurement. Within this framework, the study aims to assess Turkey's environmental sensitivity and sustainable development performance using the proposed EFM index. To achieve this goal, the study first constructs the Environmental Sensitivity Index (ESI), considering undesirable environmental pollution variables related to air, water, and soil pollution. Subsequently, the ESI is integrated with the Fuzzy Malmquist Total Factor Productivity Index (FM) to develop the new EFM index. The proposed integrated EFM index exhibits an enhanced ability to evaluate both EC and TC while addressing the challenges stemming from uncertainty. The proposed integrated EFM index indicates that the Marmara and Aegean regions of Turkey demonstrate the highest level of sustainable development performance. Finally, the study offers recommendations and policies to assist developing countries in enhancing their sustainable development performance.

Economic and Environmental Decomposition of Luenberger-Hicks-Moorsteen Total Factor Productivity Indicator: Empirical Analysis of Chinese Textile Firms With a Focus on Reporting Infeasibilities and Questioning Convexity

We discuss an environmental Luenberger&#x2013;Hicks&#x2013;Moorsteen (LHM) total factor productivity (TFP) indicator and its decomposition that incorporates a negative externality into the measurement of economic performance. Special cases of a generalized environmental directional distance function are involved in the definition of this LHM indicator and its proposed decomposition. We also seek to test whether changes in the convexity assumption provoke differences in the TFP measures. We apply two specifications of the by-production nonparametric environmental technology to implement this LHM TFP. This LHM TFP indicator decomposes into three terms representing technical change, technical inefficiency change, and scale inefficiency change. The changes in the environmental TFP for China&#x0027;s textile industry is then estimated for the period from 2001 to 2010. We report infeasibilities and we show the differences of the proposed framework for the decomposition of the LHM indicator depending on the convexity assumption. The results suggest there has been an increase in the TFP of China&#x0027;s textile industry: the amount depends on the convexity or not of the technology. The environmental performance is poorer than the economic one. Moreover, contradictions between convex and nonconvex LHM indicators for individual observations appear for a substantial part of the sample.

Evaluation of the double-cycle benefits of international engineering cooperation and the Western economy - based on the SFA methodology

Abstract In the era of globalization and development, international engineering cooperation is crucial to the improvement of economic efficiency in the West. This paper selects panel data from six regions in the West from 2019-2022 and selects reasonable input-output indicators and environmental variable indicators. At the first stage of the three-stage DEA model, the static measurement of Western economic efficiency is first measured using the variable scale compensation (BCC) model. The SFA model is utilized to decompose the slack variables during the first stage and adjust the input variables without affecting environmental variables. In addition, the Malmquist index model is used to analyze the efficiency of the Western economy dynamically in order to have a more comprehensive evaluation of the double-cycle efficiency of the Western economy from the perspective of dynamic and static. The results of the study show that after removing the effects of environmental factors and random errors, the average values of technical efficiency, pure technical efficiency, and scale efficiency in the third stage of all western regions have increased by 0.0175, 0.0193, and 0.0194 compared with those in the first stage, and the annual average total factor productivity index has shown a decreasing and then increasing trend. The SFA method used in the study can effectively eliminate the influence of environmental factors and random factors and evaluate the double-cycle efficiency situation of international engineering cooperation and the Western economy more comprehensively.

Economic Impact Analysis of Value Chain Development Programme (Vcdp) on Productivity of Rice Farmers in Niger State, Nigeria

This study evaluated economic impact analysis of value chain development programme on productivity of rice farmers in Niger State, Nigeria. Primary data were used. A multi-stage sampling technique was used to select a total sample size of two hundred and ninety-two (292) rice farmers which comprised of one hundred and fifty-five (155) value chain development program beneficiaries and one hundred and thirty-seven (137) non- beneficiaries. Data were analyzed using descriptive statistics, farm budgeting technique, total factor productivity index, Tobit dichotomous regression model, propensity score matching (PSM), principal component analysis, F-Chow test, and t-test. The results revealed that the 65.81% of the rice farmers who benefited from the value chain program were male. Also, 48.91% of the non-beneficiaries of VCDP were at sub-optimal productivity level, while 36.13% of the beneficiaries were at super-optimal productivity level. The result of the Tobit regression estimates shows that the significant factors influencing total factor productivity were: that household size (P&lt; 0.10), farm experience (P&lt; 0.10), access to credit (P&lt; 0.05), labour input (P&lt; 0.10), and farm size (P&lt; 0.10). Rice production in the study area was profitable. The coefficient of Average Treatment Effect for all matching algorithms for yields of rice farmers such as nearest neighbor, radius, kernel, and stratification were significant at (P&lt; 0.01). This shows that value chain development program impacted positively on productivity of rice farmers. Extension officers should be employed to train rice farmers. Governments should put policies in place that will help remove bottlenecks in accessing agricultural loans.

Technical efficiency in banks: a review of methods, recent innovations and future research agenda

AbstractTechnical efficiency in banking is a critical aspect of the financial industry and has been widely studied using various measurement techniques. This systematic literature review offers a comprehensive examination of 305 studies on the application of technical efficiency measurement techniques in both Islamic and conventional banking sectors from 1989 to 2019. Our comprehensive analysis not only provides a broad view of the efficiency measurement literature but also outlines a future research agenda. Despite the extensive research in this field, several issues remain unresolved, including input–output selection, a comparison of efficiency between Islamic and conventional banks, limited cross-country studies, and a lack of exploration into the impact of regulation and Shariah principles. To address these gaps, this review highlights the most commonly used methods, variables, and findings and provides three key recommendations for future research. Three key themes emerge from our examination. First, there is a need to better understand and the application of new frontier techniques other than the traditional methods, which currently dominate the existing literature. Second, the intermediation approach is the most frequently used in variable selection, thus more studies with comparative findings with applications of production and value-added approaches are suggested. Third, the most frequently used input variables are ‘labor’, ‘deposits’ and ‘capital’, whilst ‘loans’ and ‘other earning assets’ are the most popular output variables. We recommend three vital directions for future research: (i) non-interest expenses to be included amongst the inputs, while non-interest income should be added to the list of outputs, especially when estimating efficiency scores of Islamic banks. (ii) The impact of environmental variables such as, inter alia, Shariah principles, country-specific factors, and management quality is suggested to be considered simultaneously in models measuring and comparing the efficiency of Islamic and conventional banks. (iii) The selection of performance metrics employed should be expanded to include both the standard efficiency scores and the Malmquist Total Factor Productivity Index (TFP). The paper concludes with research needs and suggests directions for future research.

The effects of environmental pollution on food security in Malaysia

Environmental pollution has emerged as a critical global challenge, significantly affecting various aspects of human life, including food security. This research paper investigates the effects of environmental pollution on agricultural output (a proxy for food security) in Malaysia from 1990 to 2020, utilising the Autoregressive Distributed Lag (ARDL) method. The results obtained from the bounds cointegration testing approach provided strong evidence supporting the existence of a long-term relationship among Methane emissions in the energy sector (thousand metric tons of CO2 equivalent) (CH4), Carbon dioxide emissions (metric tons per capita) (CO2), Nitrous oxide emissions in the energy sector (thousand metric tons of CO2 equivalent) (N2O), GDP, population, index of agricultural total factor productivity, and agricultural output. Estimation of long-run and short-run ARDL with diagnostic and model stability reveals that there is a positive correlation between the index of agricultural total factor productivity (TFP) and agricultural output in Malaysia in all four of the models analysed. The discoveries illuminate the possible mechanisms by which environmental pollution affects food security in Malaysia, offering valuable insights to policymakers and stakeholders for crafting effective strategies toward sustainable development. By uncovering the implications of environmental degradation on food availability, access, and nutritional quality, the study highlights the urgency of addressing environmental challenges to ensure long-term food security for the Malaysian population. Moreover, the study can serve as a basis for formulating sustainable policies that promote resource conservation, waste management, and eco-friendly practices in the agricultural and industrial sectors, fostering a harmonious coexistence between economic development and environmental preservation.

Efficiency Analysis with Data Envelopment Analysis and Malmquist Total Factor Productivity Index: An Implementation in Group a Hospitals

Sağlık hizmet sunumunda kritik role sahip kurumlar olan hastanelerin üretim süreçlerindeki etkinliklerinin sağlanması bir gerekliliktir. Bu araştırma ile Türkiye’de kullanılan hastane sınıflandırma sistemine göre A-1 ve A-2 grubu hastanelerin 2018-2020 yıllarına ait verilerini kullanarak bulundukları illerin sağlık alanındaki etkinliklerinin ölçülmesi ve etkinliklerinin yıllar içerisindeki değişimlerinin ortaya çıkarılması amaçlanmıştır. Bu amaçla, araştırmada non-parametrik bir yöntem olan Veri Zarflama Analizi (VZA) ve Malmquist Toplam Faktör Verimlilik İndeksi (MTFVİ) yöntemleri kullanılmıştır. A-1 grubundaki illerin ölçeğe göre sabit getiri varsayımı altında yapılan VZA’ne göre (CCR modeli) üç yıl için sırasıyla %53,1; %53,1; %56,2’si etkindir. Ölçeğe göre değişken getiri varsayımı altında (BCC Modeli) yapılan analize göre ise etkin olan illerin oranı %65,6; %68,7; %75’tir. Bu iki analiz sonucunda etkin olmayan iller için örnek almaları gereken iller belirlenmiş ve etkin sınırda üretim için girdi değişkenlerinde yapılması gereken değişiklikler ile ilgili önerilerde bulunulmuştur. MTFVİ sonuçlarına göre, 2018-2019 periyodunda 24 ilin; 2019-2020 periyodunda 8 ilin toplam faktör verimliliklerinde iyileşme olduğu görülmüştür. A-2 grubunda ise CCR modeline göre illerin %45,4, %36,3 ve %27,2’si; BCC modeline göre %66,6, %63,6 ve % 45,4’ü etkindir. MTFVİ sonuçlarına bakıldığında ise, 2018-2019 periyodunda 23; 2019-2020 periyodunda ise 17 ilin toplam faktör verimliliklerinde iyileşme olmuştur. Her iki periyotta da bu iyileşmelerin kaynağının neredeyse tüm illerde sadece teknolojik ilerlemeler olduğu sonucuna ulaşılmıştır.&#x0D; Anahtar Kelimeler: Etkinlik Analizi, Veri Zarflama Analizi, Malmquist Toplam Faktör Verimlilik İndeksi&#x0D; JEL Sınıflandırması: D24, I10, G20

Health systems efficiency in China and ASEAN, 2015–2020: a DEA-Tobit and SFA analysis application

ObjectiveTo evaluate the health systems efficiency in China and Association of Southeast Asian Nations (ASEAN) countries from 2015 to 2020.DesignHealth efficiency analysis using data envelopment analysis (DEA) and stochastic frontier...

Greening the digital revolution: assessing the impact of digital transformation on green total factor productivity in Chinese enterprises.

The green digital revolution has changed the production mode of enterprises. This article explores the green value of digital transformation. The study calculates the digital transformation index and green total factor productivity (EGTFP) index of Chinese enterprises from 2012 to 2021 and uses a panel data model and intermediary effect to conduct empirical tests. The results show that digital transformation has a positive impact of 0.371 units on the EGTFP. This positive effect is proven to be stable after distinguishing between substantive and tactical digital transformation, where the effect of substantive digital transformation increases over time. At the same time, enterprise property rights and location affect the role of digital transformation; moreover, digital transformation performs better when grouping the nonstate-owned enterprises and the eastern region. In addition, energy efficiency, green technology innovation, and environmental responsibility are important intermediaries, as digital transformation can affect EGTFP by improving energy efficiency, promoting green technology innovation, and strengthening environmental responsibility. These research conclusions help evaluate the economic and environmental effects of digital transformation and provide empirical evidence for the high-quality development of enterprises.

Evaluation of Urban Flood Governance Efficiency Based on the Data Envelopment Analysis Model and Malmquist Index: Evidence from 30 Provincial Capitals in China

Urban flooding disasters endanger people’s lives and property while causing significant economic damage to cities. To further improve the efficiency of urban flooding governance and promote the optimal allocation of resources, this article selects the number of people in flood control, medical and health security, financial expenditure on flood control, affected population, and direct economic loss as evaluation indicators from the input–output perspective; it measures the efficiency of urban flooding governance in 30 provincial capitals in China from 2012 to 2021 using the DEA model and Malmquist index method and identifies the key factors affecting the efficiency of urban flooding governance. The research results show that in 2021, the average value of the comprehensive technical efficiency of flood disaster governance in 30 provincial capitals in China was 0.408, the development trend was not optimistic, and the constraint factor was scale efficiency. The interannual average value of the total factor productivity index of urban flood disaster governance from 2012 to 2021 was 0.976, and the overall trend was decreasing year by year, during which some cities were able to achieve a yearly increase in governance efficiency, but most cities still faced a severe situation in flood disaster governance. The total factor productivity index varied enormously across towns with the variation in annual precipitation; the greater the annual precipitation, the greater the total factor productivity index of urban flooding disaster governance in the urban agglomerations, and the comprehensive technical efficiency change was consistent with its trend change. This consistency has a positive contribution to the total factor productivity index of urban flooding disaster governance.

Impact of Climate Change on Total Factor Productivity of Agriculture in District Multan

Agriculture is particularly vulnerable to climate change because it faces open weather conditions. In uncontrolled open weather circumstances, it's difficult to attain better total factor productivity (TFP), which characterizes agriculture growth in an economy. The study estimated the TFP growth of Pakistan’s agriculture in first step by employing the Tornqvist- Theil index number approach for the period 1990-2019. The time series data for thirteen crops and four livestock categories from 1990 to 2019 were collected from different sources to estimate the TFP. The average annual TFP growth of agriculture was estimated to be 2.14 percent for the study period, and it contributed about 56 percent to total agricultural output growth. The results also indicated that TFP growth in agriculture sector was highest (0.05 percent) during the 1990-2000, while lowest (-2.14 percent) during the last decade. After, TFP index that was calculated in first step was used as dependent variable in second step of analysis. Then we estimated the impact of climate change on TFP in agriculture sector in Multan district. For this first we used ARDL bound test approach for estimation of long run impact of climatic variables. The results showed that there are positive effects of both minimum and maximum temperature on TFP in the study area. The drought and floods have negative impact on TFP but in first lag their effects became positive on TFP. One of the important variables of climate is rain that had positive impact on the TFP growth, with 1% increase in rainfall there was 0.22% increase in TFP at first lag. Improving the adaptation and mitigation practices related to floods and droughts would be required for sustainable growth in TFP in agriculture sector in Multan District.