The long-run relationship between farm size and productivity

2019 ◽  
Vol 11 (2) ◽  
pp. 373-386
Author(s):  
Wanjun Yao ◽  
Shigeyuki Hamori
Keyword(s):  
Panel Data ◽  
Inverse Relationship ◽  
Agricultural Productivity ◽  
Farm Size ◽  
Land Productivity ◽  
Content Type ◽  
Long Run ◽  
The Difference ◽  
The Relationship

Purpose The purpose of this paper is to examine the long-term relationship between farm size and productivity in China at the national level. Design/methodology/approach In contrast to the micro-data examination conducted by earlier literature, in this study, the authors use household aggregate panel data on 29 provinces in China for 1988–2012. Using the panel data PMG model, the authors control the factor of difference in land quality due to the fixed effect in each province, and the authors consider the difference in the long-run coefficients of farm size and land productivity rather than the difference in their short-run relationship. Thus, the authors examine the long-term relationship between farm size and productivity. Furthermore, the authors examine the robustness of this relationship in the long-term using samples of rice, wheat and corn production by region. Findings In contrast with the findings presented previously, the authors find that the relationship between farm size and agricultural productivity is statistically positive in the long term. Originality/value The relationship between farm size and agricultural productivity is a key research issue in agricultural and development economics. In China, many studies have provided evidence of the inverse relationship between farm size and agricultural productivity at the family farm level. However, this inverse relationship seems to reflect specific regions and specific periods in the relationship between farm size and land productivity. At the nationwide level, in the long-term, this is not an inverse but a positive relationship. It is desirable to expand farm size for the long-term development of agriculture.

Exchange rate volatility and exports from India: a commodity-level panel data analysis

2019 ◽  
Vol 12 (1) ◽  
pp. 23-44
Author(s):  
Chandan Sharma
Keyword(s):  
Exchange Rate ◽  
Panel Data ◽  
Exchange Rate Volatility ◽  
Nominal Exchange Rate ◽  
Exchange Rate Risk ◽  
Content Type ◽  
Long Run ◽  
Short Run ◽  
The Relationship

PurposeThis study aims to examine the relationship between exchange rate risk and export at commodity level for the Indian case.Design/methodology/approachThe monthly panel data used for analysis are at a disaggregated level, which cover around 100 products, encompassing all merchandize sectors for the period spanning from 2012:12 to 2017:11. To measure the exchange rate volatility, the authors use real as well as nominal exchange rate concepts and predict the volatility of exchange rate using the autoregressive conditional heteroscedastic-based model. They use pooled mean group, mean group and common correlated effects mean group estimator that is suitable for the objectives and data frequency.FindingsThe empirical analysis indicates both short- and long-term negative effects of exchange rate variations on exporting. Specifically, in the long run, real exchange rate as well as nominal exchange rate volatility has significant effects on export performance, yet, the effects of uncertainty of nominal exchange rate is much severe and intense. In the short run, it is the nominal exchange rate uncertainty that hurts exports from India. Nevertheless, the short-run effect is much lesser than the long-run, supporting the argument that the short-term exchange rate risk can be hedged, at least partially, through financial instruments; however, uncertainty of the long-term horizon cannot be hedged easily and cost-effectively.Practical implicationsReducing uncertainty and attaining stability in exchange rate and price level should be an important policy objective in developing countries such as India to achieve higher export growth, both in the short and long run.Originality/valueUnlike previous studies, this paper tests the relationship using micro-level data and uses advanced econometric techniques that are likely to provide more precise information regarding the association between exchange rate volatility and trade flows.

Analyzing the relationship between exploration, exploitation and organizational innovation

2017 ◽  
Vol 21 (5) ◽  
pp. 1142-1162 ◽  
Author(s):  
Manuel Guisado-González ◽  
Jennifer González-Blanco ◽  
José Luis Coca-Pérez
Keyword(s):  
Panel Data ◽  
Organizational Innovation ◽  
Sample Selection ◽  
Exploration And Exploitation ◽  
Content Type ◽  
Long Run ◽  
Using Data ◽  
Exploration Exploitation ◽  
The Relationship ◽  
Organizational Innovations

Purpose Although most of the literature supports the existence of a substitutive relationship between exploration and exploitation, some authors suggest that this relationship is complementary (ambidexterity), and others argue that there is no relationship. This paper aims to introduce organizational innovation into the analysis and discusses which of these three relationships prevails. Design/methodology/approach Analyses were performed using data from Spanish Technological Innovation Panel for the period 2008-2013. It should be emphasized that the use of panel data is essential in the analysis of the interaction of exploration and exploitation, as exploration only makes sense in the long run. Econometric strategy uses a two-stage selection model, estimated using the Wooldridge’s (1995) consistent estimator for panel data with sample selection. To perform the test, the hypothesis uses the approach of complementarity. Findings The results show that the relationships exploration-organizational innovation and exploitation-organizational innovation are complementary, provided that the analysis is performed on companies that simultaneously carry out exploration and exploitation activities, respectively. This indicates that the achievement of ambidexterity is strongly conditioned by the simultaneous realization of organizational innovations. Practical implications Managers and policymakers should be aware that the simultaneous implementation of exploration and exploitation yields better results when the corresponding organizational innovations are also implemented. Originality/value This paper extends the empirical investigation of the relationship between exploration and exploitation, seen in conjunction with organizational innovation, and using the complementarity approach as a research tool.

The influence of cultural values on green purchase behaviour

2017 ◽  
Vol 35 (3) ◽  
pp. 377-396 ◽  
Author(s):  
The Ninh Nguyen ◽  
Antonio Lobo ◽  
Steven Greenland
Keyword(s):  
Cultural Values ◽  
Purchase Intention ◽  
Structural Equation ◽  
Current Knowledge ◽  
Environment Friendly ◽  
Content Type ◽  
Long Run ◽  
Personal Level ◽  
The Relationship

Purpose The purpose of this paper is to investigate the influence of consumers’ collectivism and long-term orientation (LTO) cultural values on their purchase intention in relation to environment-friendly products. Design/methodology/approach This research adopts a hypo-deductive research design. A unique conceptual model was developed by linking cultural values to key determinants of green purchase behaviour. This model was then tested using a quantitative survey of 682 shoppers in popular Vietnamese electrical appliance stores. Findings Analysis using structural equation modelling reveals that consumers with greater adherence to collectivism and LTO tend to engage in green purchase behaviour owing to their positive environmental attitudes, strong subjective norms and tolerance of inconvenience associated with eco-friendly product purchase. Gender is found to moderate the relationship between the determinants and purchase intention. Practical implications Marketers including manufacturers and policymakers must endeavour (change globally) to reduce or eliminate perceived inconvenience associated with green purchases. They should also effectively communicate messages stressing that eco-friendly product purchases are crucial for environmental protection and benefit consumer groups including family, peers and society in the long-run. Originality/value This research is the first of its kind which links consumers’ cultural values at a personal level to all the elements of the theory of planned behaviour. This research also extends current knowledge about green purchase behaviour in emerging markets by focussing on Vietnam.

Farm size and use of inputs: explanations for the inverse productivity relationship

2019 ◽  
Vol 11 (2) ◽  
pp. 336-354
Author(s):  
Shen Cheng ◽  
Zhihao Zheng ◽  
Shida Henneberry
Keyword(s):  
Empirical Studies ◽  
Value Added ◽  
Policy Implications ◽  
Farm Size ◽  
Land Productivity ◽  
Data Set ◽  
Content Type ◽  
Demand Models ◽  
Labor Inputs ◽  
The Relationship

Purpose The relationship between farm size and land productivity is a hotly debated issue in the study of agricultural economics and development economics. The purpose of this paper is to explore the causes leading to the inverse productivity relationship by examining the relationship between farm size and factor inputs. Design/methodology/approach With a large panel data set of farm households in China during 2010–2011, this study uses the factor demand models to examine the relationship between farm size and per-mu labor and non-labor inputs while employing a stochastic frontier production function in determining the difference of labor efforts in farming operation across farm sizes. Moreover, the models for value-added margins and profits are used to further determine producer behavior of small-size farms. Findings Results of this study show that, as compared to larger farms, smaller farms not only utilize more labor and non-labor inputs per mu, but also benefit from a higher labor effort. Moreover, smaller farms concentrate more on grain output and cash costs while focusing less on the family labor input costs in an effort to maximize value-added margins rather than profits. The higher yields on smaller farms are thus a result of the utilization of a relatively higher level of labor and non-labor inputs along with skilled-oriented precision farming technology. The inverse productivity relationship is explained by the behavior of small-size producers with employment constraints, leading to smaller farms generating a higher yield than larger farms. Originality/value While Sen (1966), Feder (1985), Eswaran and Kotwal (1986) and others have theoretically derived the causal relationship between the incomplete factor markets, especially incomplete labor markets, and the inverse productivity, empirical studies to test the causal relationships are limited. In particular, a solid foundation based on an empirical analysis is lacking when it comes to explaining the inverse productivity in China. Results of this study are expected to have significant policy implications in terms of the understanding of small-size producer behavior and the associated mechanism underlying the inverse relationship between farm size and land productivity.

To examine the relationships between supplier development practices and supplier-buyer relationship practices from the supplier’s perspective

2017 ◽  
Vol 24 (5) ◽  
pp. 1309-1336 ◽  
Author(s):  
Sarang Joshi ◽  
Manoj Kharat ◽  
Rakesh Raut ◽  
Sachin Kamble ◽  
Sheetal Kamble
Keyword(s):  
Structural Equation ◽  
Success Factors ◽  
Structural Model ◽  
Manufacturing Firms ◽  
Supplier Development ◽  
Competitive Advantages ◽  
Content Type ◽  
The Relationship ◽  
Relationship Improvement

Purpose The purpose of this paper is to examine the relationships between supplier development practices (SDPs) and supplier-buyer relationship practices from the supplier’s perspective (SBRSP), and seek to understand how specific SDPs may impact a buyer’s operational performance as well as supplier-buyer relationship practices. Design/methodology/approach The authors conducted a survey of 512 respondents from the different manufacturing firms in India and applied structural equation modelling to test a structural model that proposes the impacts of various efforts of SDPs on a buyer’s performance as well as SBRSP. Findings The study concludes that SDPs and SBRSP together improve the relationship between a buyer and supplier, and this improved relationship leads to competitive advantages (CAs) followed by profitability. Results indicate that supplier perspective of buyer-supplier relationship can be improved under the condition of SDPs and SBRSP together. SDPs are driven by productive measure and competitive pressure, whereas customer uncertainty is found to be statistically insignificant. Research limitations/implications The study was carried out in North Maharashtra Industrial Zone of India, where the auto sector and machine/components manufacturing firms have been established for a considerable period of time. Results of the study are limited to manufacturing organizations predominantly focussing on the automobile sector and machine/components manufacturing firms. Practical implications This study provides significant insights into the specific impact of various SDPs and SBRSP for both academics and practitioners. SDPs along with SBRSP practices lead to improvement in the relationship leading to CAs. SBRSP suggests that trust, long-term commitments and the supplier’s perspective are important practices for relationship improvement. Originality/value The current study attempts to identify what are the success factors for the supplier-buyer relationship from the supplier’s perspective and SDPs and how the supplier-buyer relationship can be improved under the condition of SDPs and SBRSP. Hence, the aim is to develop a more thorough understanding of the outcomes of a supplier-buyer relationship improvement from both buyer’s and supplier’s perspective, under the conditions of supplier development to achieve CAs leading to profitability. Furthermore, the study analyses the effect of the improved supplier-buyer relationship for achieving CAs leading to profitability.

Long run apartment price dynamics in Swedish and German cities

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sviatlana Engerstam
Keyword(s):  
Banking Sector ◽  
Cointegration Analysis ◽  
Price Dynamics ◽  
Long Term Effects ◽  
Content Type ◽  
Macroeconomic Variables ◽  
Price Elasticities ◽  
Long Run ◽  
German Cities

PurposeThis study examines the long term effects of macroeconomic fundamentals on apartment price dynamics in major metropolitan areas in Sweden and Germany.Design/methodology/approachThe main approach is panel cointegration analysis that allows to overcome certain data restrictions such as spatial heterogeneity, cross-sectional dependence, and non-stationary, but cointegrated data. The Swedish dataset includes three cities over a period of 23 years, while the German dataset includes seven cities for 29 years. Analysis of apartment price dynamics include population, disposable income, mortgage interest rate, and apartment stock as underlying macroeconomic variables in the model.FindingsThe empirical results indicate that apartment prices react more strongly on changes in fundamental factors in major Swedish cities than in German ones despite quite similar development of these macroeconomic variables in the long run in both countries. On one hand, overreactions in apartment price dynamics might be considered as the evidence of the price bubble building in Sweden. On the other hand, these two countries differ in institutional arrangements of the housing markets, and these differences might contribute to the size of apartment price elasticities from changes in fundamentals. These arrangements include various banking sector policies, such as mortgage financing and valuation approaches, as well as different government regulations of the housing market as, for example, rent control.Originality/valueIn distinction to the previous studies carried out on Swedish and German data for single-family houses, this study focuses on the apartment segment of the market and examines apartment price elasticities from a long term perspective. In addition, the results from this study highlight the differences between the two countries at the city level in an integrated long run equilibrium framework.

A multifractal detrended fluctuation analysis of housing market: a role of financial crises in developed economies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Syed Ali Raza ◽  
Nida Shah ◽  
Muhammad Tahir Suleman ◽  
Md Al Mamun
Keyword(s):  
Financial Crisis ◽  
Housing Market ◽  
Market Efficiency ◽  
House Price ◽  
Fluctuation Analysis ◽  
Content Type ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Long Run ◽  
Before And After

Purpose This study aims to examine the house price fluctuations in G7 countries by using the multifractal detrended fluctuation analysis (MF-DFA) for the years 1970–2019. The study examined the market efficiency between the short-term and long-term in the full sample period, before and after the global financial crisis period. Design/methodology/approach This study uses the MF-DFA to analyze house price fluctuations. Findings The findings confirmed that the housing market series are multifractal. Furthermore, all the markets showed long-term persistence in both the short and long-term. The USA is identified as the most persistent house market in the short run and Japan in the long run. Moreover, in terms of efficiency, Canada is identified as the most efficient house market in the long run and the UK in the short run. Finally, the result of before and after the financial crisis period is consistent with the full sample result. Originality/value The contribution of this study in the literature is fourfold. This is the first study that has examined the house prices efficiency by using the MF-DFA technique given by Kantelhardt et al. (2002). Previously, the house market prices and efficiency has been investigated using generalized Hurst exponent (Liu et al., 2019), Quantile Regression Approach (Chae and Bera, 2019; Tiwari et al., 2019) but no study to the best of the knowledge has been done that has used the MF-DFA technique on the housing market. Second, this is the first study that has focused on the house markets of G7 countries. Third, this study explores the house market efficiency by dividing the market into two periods i.e. before and after the financial crisis. The study strives to investigate if the financial crisis determines the change in the degree of market efficiency or not. Finally, the study gives valuable insights to the investors that will help them in their investment decisions.

Tornadoes, poverty and race in the USA: A five-decade analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Russ D. Kashian ◽  
Tracy Buchman ◽  
Robert Drago
Keyword(s):  
African American ◽  
African Americans ◽  
Study Finding ◽  
Median Income ◽  
Content Type ◽  
Vulnerable Communities ◽  
Long Run ◽  
Level Data ◽  
The Usa

PurposeThe study aims to analyze the roles of poverty and African American status in terms of vulnerability to tornado damages and barriers to recovery afterward.Design/methodology/approachUsing five decades of county-level data on tornadoes, the authors test whether economic damages from tornadoes are correlated with vulnerability (proxied by poverty and African American status) and wealth (proxied by median income and educational attainment), controlling for tornado risk. A multinomial logistic difference-in-difference (DID) estimator is used to analyze long-run effects of tornadoes in terms of displacement (reduced proportions of the poor and African Americans), abandonment (increased proportions of those groups) and neither or both.FindingsControlling for tornado risk, poverty and African American status are linked to greater tornado damages, as is wealth. Absent tornadoes, displacement and abandonment are both more likely to occur in urban settings and communities with high levels of vulnerability, while abandonment is more likely to occur in wealthy communities, consistent with on-going forces of segregation. Tornado damages significantly increase abandonment in vulnerable communities, thereby increasing the prevalence of poor African Americans in those communities. Therefore, the authors conclude that tornadoes contribute to on-going processes generating inequality by poverty/race.Originality/valueThe current paper is the first study connecting tornado damages to race and poverty. It is also the first study finding that tornadoes contribute to long-term processes of segregation and inequality.

MERGE OF THE TECHNİCAL ANALYSİS TYPES GİVES THE BEST RESULTS İN CRYPTOCURRENCY MARKET

2021 ◽  
Vol 6 (14) ◽  
pp. 89-97
Author(s):  
MUSTAFA ÖZYEŞİL ◽  
MOHAMMAD AL-TARIFI
Keyword(s):  
Supply And Demand ◽  
Investment Strategy ◽  
Proof Of Concept ◽  
Market Capitalization ◽  
Long Run ◽  
Peer Network ◽  
Tangible Asset ◽  
The Relationship ◽  
Peer To Peer Network

Cryptocurrencies are a modern kind of financial instrument (Hudson & Urquhart, 2019), the first cryptocurrency is Bitcoin , proposed by who called Satoushi Nakamato (2008), as The open source was created on the proof-of-concept principle that transactions can be securely treated on a decentralized peer to peer network without the need for a central clearinghouse, which appeared 2009 ( Heid, 2013). The success of the bitcoin blazes a trail to what called ‘Altcoin” this expression means all the cryptocurrencies that set in motion after the victory of the bitcoin, these coins sell themselves as the best alternatives for the bitcoin (FRANKENFIELD, 2020) . There are many types for the altcoin. The third type of the cryptocurrency is called Tokens Unlike Bitcoin and Altcoins, tokens are not able to activate independently and are dependent on the grid of another cryptocurrency. That means they do not have their own core DLT or blockchain, but instead, are built on top of an existing cryptocurrency’s blockchain (Types of cryptocurrencies: explaining the major types of cryptos, 2019). The worth of bitcoin doesn’t depend on any tangible asset or economies of the countries while it is based upon the security of an algorithm which traces all transactions (Hudson & Urquhart, 2019). The studies determine the number of the bitcoin price development in the long -run (Ciaian, Rajcaniova, & Kancs, 2018): • Market forces of the Bitcoin supply and demand • The bitcoin’s attractiveness for the investors • The influence of global macro-financial developments If you're forming an investment strategy designed to help you trail long-term financial intentions, understanding the relationship between company size, return potential, and risk is vital. (Market cap—or market capitalization—refers to the total value of all a company's shares of stock, 2017) .Hence , Manifested importance a cryptocurrency’s market capitalization as the total values of all coins currently in circulation. the cryptocurrency’s market cap contains what’s called Bitcoin Dominance that is the ratio between the market cap of bitcoin to other coins of the cryptocurrency markets (jacobcanfield, 2019) . Cryptocurrency trade is attractive type of investment. this market treated the same of the foreign exchange and stock market ( Radityo, Munajat, & Budi, 2017). The investors using the same basic in investment (buy low, sell high) but they need to calculating the risks

The relationship between financial development and economic growth in Eswatini (formerly Swaziland)

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Siphe-okuhle Fakudze ◽  
Asrat Tsegaye ◽  
Kin Sibanda
Keyword(s):  
Economic Growth ◽  
Granger Causality ◽  
Financial Development ◽  
Granger Causality Test ◽  
Causality Test ◽  
Content Type ◽  
Distributed Lag ◽  
Long Run ◽  
Short Run ◽  
The Relationship

PurposeThe paper examined the relationship between financial development and economic growth for the period 1996 to 2018 in Eswatini.Design/methodology/approachThe Autoregressive Distributed Lag bounds test (ARDL) was employed to determine the long-run and short-run dynamics of the link between the variables of interest. The Granger causality test was also performed to establish the direction of causality between financial development and economic growth.FindingsThe ARDL results revealed that there is a long-run relationship between financial development and economic growth. The Granger causality test revealed bidirectional causality between money supply and economic growth, and unidirectional causality running from economic growth to financial development. The results highlight that economic growth exerts a positive and significant influence on financial development, validating the demand following hypothesis in Eswatini.Practical implicationsPolicymakers should formulate policies that aims to engineer more economic growth. The policies should strike a balance between deploying funds necessary to stimulate investment and enhancing productivity in order to enliven economic growth in Eswatini.Originality/valueThe study investigates the finance-growth linkage using time series analysis. It determines the long-run and short-run dynamics of this relationship and examines the Granger causality outcomes.

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