The Economies Scale of Agricultural Product Processing Companies Listed on Stock Exchange in Hochiminh City and Hanoi, Vietnam

This study applied the Cobb-Douglas production function to identify economics efficiency of 18agricultural product processing companies listed on the Stock exchange in Ho Chi Minh City(HOSE) and Hanoi (HNX) in such sectors as fisheries, rubber and sugar in the period 2009-2013.The method employed FEM and REM models using panel data. The results showed thatperformance of all and each sector in this study has increasing returns to scale. In particular,firms in the sectors of fisheries and rubber primarily relied on raising capital to increasetheiroutput value, while those in the sugar sectormainly increase labors toimprove theiroutput value. Finally, the paper also provides some policy implications to improve theefficiency of capital and labor in the agricultural product processing companies.

Commuting network effect on urban wealth scaling

Urban scaling theory explains the increasing returns to scale of urban wealth indicators by the per capita increase of human interactions within cities. This explanation implicitly assumes urban areas as isolated entities and ignores their interactions. Here we investigate the effects of commuting networks on the gross domestic product (GDP) of urban areas in the US and Brazil. We describe the urban GDP as the output of a production process where population, incoming commuters, and interactions between these quantities are the input variables. This approach significantly refines the description of urban GDP and shows that incoming commuters contribute to wealth creation in urban areas. Our research indicates that changes in urban GDP related to proportionate changes in population and incoming commuters depend on the initial values of these quantities, such that increasing returns to scale are only possible when the product between population and incoming commuters exceeds a well-defined threshold.

Efficiency in Utilization of the Resources Allocated to Lower Level Health Facilities in Uganda: a Case Study of Health Centre IVs

Background: Everyone has a right to quality life with good health of the household and, thus, health sector financing should be a top priority because when the population is healthy, it is very productive and wealthy. In Uganda, Health Centre IVs (HCIVs) created under Uganda National Minimum Health Care Package provide curative, prevention and promotion services. The efficiency of these HCIVs is as critical as people’s health and this paper measures efficiency in utilization of resources allocated to them.Methods: The study used Hospital and HCIV Census data for 2014 and health sector data for FY2015/16 reported by MOH in the Annual Health Sector Performance Report. STATA software was used to perform Data Envelopment Analysis for a preferred model was out-put oriented that optimizes variable returns to scale. In this way, efficiency scores for every HCIV were calculated. Also, a Tobit regression model was run to estimate the factors contributing to the adjusted inefficiency scores for HCIVs.Results: Overall, 7 HCIVs (23.3%) were operating under constant returns to scale, implying that they were efficient (both pure technical and scale efficiency) while the 19 (63.3%) were operating under increasing returns to scale, implying that their health service outputs would increase by a greater proportion compared to any proportionate increase in health services if more inputs were added in the facility. Four HCIVs (13.3%) were operating at decreasing returns to scale meaning an additional input to the HCIVs would produce a less proportional change of outputs. The study identified catchment population, average length of stay, bed occupancy rate, and outpatient department visits as a proportion of inpatient days as the main factors of efficiency among HCIVs.Conclusions: This study has shown how Data Envelope Analysis methods can be applied at the HCIV level of the health system to gain an insight into variation in efficiency across health centers using routinely available data. And, with the majority of HCIVs operating at increasing returns to scale, it showed that there is a need to increase inputs like staff, medicines and beds to achieve the desired optimal scale in case of constant returns to scale.

A DEA approach for merging dairy farms

This paper proposes a model for determining the most advantageous merger within a set of dairy farms. It uses data envelopment analysis (DEA) to estimate the total technical efficiency improvement that the merger would produce and for decomposing it into a learning effect and a pure merger effect. A design of experiments has also been carried to test the effects of various factors (the total number of farms, the standard deviation of herd size, the percentage of farms exhibiting increasing returns to scale, the standard deviation of the current technical efficiency of the farms) on different response variables (the percentage of farms involved in the merger, the reduction of herd size and the efficiency improvement obtained by the merger). The results show that the disparity in the herd size of the farms in a region and the percentage of farms that exhibit increasing returns to scale increase the number of farms that enter into the most advantageous merger. The disparity of herd size also increases the number of cows that are not needed after the merger. Finally, the expected efficiency improvement increases with the total number of farms.

EQUILIBRIUM INDETERMINACY, ENDOGENOUS ENTRY AND EXIT, AND INCREASING RETURNS TO SPECIALIZATION

This paper systematically examines the interrelations between equilibrium indeterminacy, endogenous entry and exit of intermediate input firms, and increasing returns to specialization within two versions of a parsimonious one-sector monopolistically competitive RBC model. The technology for producing an intermediate good is postulated to display internal increasing returns to scale in our benchmark framework, whereas positive productive externalities are considered in the alternative setting. We analytically show that either formulation will exhibit belief-driven cyclical fluctuations provided the equilibrium wage-hours locus is positively sloped and steeper than the household’s labor supply curve. We also find that ceteris paribus our alternative macroeconomy is more susceptible to indeterminacy and sunspots than the baseline counterpart.

Association between population distribution and urban GDP scaling

Urban scaling and Zipf’s law are two fundamental paradigms for the science of cities. These laws have mostly been investigated independently and are often perceived as disassociated matters. Here we present a large scale investigation about the connection between these two laws using population and GDP data from almost five thousand consistently-defined cities in 96 countries. We empirically demonstrate that both laws are tied to each other and derive an expression relating the urban scaling and Zipf exponents. This expression captures the average tendency of the empirical relation between both exponents, and simulations yield very similar results to the real data after accounting for random variations. We find that while the vast majority of countries exhibit increasing returns to scale of urban GDP, this effect is less pronounced in countries with fewer small cities and more metropolises (small Zipf exponent) than in countries with a more uneven number of small and large cities (large Zipf exponent). Our research puts forward the idea that urban scaling does not solely emerge from intra-city processes, as population distribution and scaling of urban GDP are correlated to each other.

Returns to Scale as an Established Scaling Indicator: Always a Good Advisor?

In data envelopment analysis (DEA), returns to scale (RTS) are a widely accepted instrument for a company to reveal its activity scaling potentials. In the case of increasing returns to scale (IRS), a company learns that upsizing activities improves its productivity. For decreasing returns to scale (DRS), the instrument likewise should depict a downsizing force, again for improving productivity. Unfortunately, here the classical RTS concept shows misbehavior. Under certain circumstances, it is the wrong indicator for scaling activities and even hides respective productivity improvement potentials. In this paper, we study this phenomenon, using the DEA concept, and illustrate it via little numerical examples and a real-world application consisting of 37 Brazilian banks.