Local Prices Research Articles

Does the Sleman Chili Auction Market Affect the Local, Regional and National Market Prices in Indonesia?

Promoting the horticultural auction market as an alternative outlet is becoming more popular. The horticultural auction market has some benefits, such as reducing price volatility and controlling inflation. This research used a case study in Sleman Regency, which established a horticultural auction market to manage volatile chili prices. The daily price data with ECM-GARCH analysis was used to investigate market integration between the Sleman chili auction market and other markets. The result showed that the Sleman auction market had a beneficial impact on the price decline in the local markets. This impact indicated that the auction market controls inflation at the regional level. However, only 5% to 13% of daily variations of the long-term equilibrium of the auction market to other markets were adjusted. There was information efficiency of the chili prices in Indonesia based on the GARCH model. This study proves that auction markets promote control of macro inflation. This study was the first to manage horticultural product price risk from a chili auction market perspective. Moreover, the model applied in this study expands the ECM-GARCH model to improve the validity of an ECM's significance tests and the efficiency of standard ECM parameter estimation.

Gains from monetary policy cooperation under asymmetric currency pricing

In most international trade transactions, the U.S. dollar is used. Hence, this study considers optimal monetary policy in a two-country model under asymmetric currency pricing (ACP) in which U.S. (Home) firms use producer currency pricing (PCP) while firms in the rest of the world (Foreign) use local currency pricing (LCP). In the ACP model, there is an additional inefficiency, namely, the internal relative price distortion compared with the LCP model and the distortion arising from deviations from the law of one price compared with the PCP model. Consequently, welfare gains from monetary policy cooperation in the ACP model are substantially greater compared with the LCP and PCP models. Moreover, the noncooperative Foreign policymakers in the ACP model can manipulate not only the internal relative price but also deviations from the law of one price in favor of their own welfare through nominal exchange rate adjustment, whereas the noncooperative Home policymakers can control neither. This result rationalizes the fact that the U.S. designates currency manipulators to protect its welfare. Therefore, gains from cooperation in Home are larger than in Foreign. Furthermore, I find that there are substantial gains from cooperation in the ACP model even under the conditions that remove gains from cooperation in the LCP and PCP models.

How does environmental pollution affect housing price

Environmental quality and housing prices have become two hot topics closely related to people's lives. When choosing housing, residents pay more and more attention to the quality of the surrounding environment. However, in view of the differences in living standards, there are huge regional differences in economic conditions and air pollution in different regions, resulting in different distributions of immigration rates, and immigration rates have a significant impact on housing prices. This article discusses the difference in immigration rate caused by environmental pollution and its impact on housing prices from a spatial perspective. In this article, we use the GIS system to analyze the impact of environmental pollution on an immigration rate. We use Chicago's immigration rate, economic conditions, pollution and other GIS data to show that environmental pollution is relevant to the immigration rate. People are willing to relocate to areas with low levels of environmental pollution. Then we use the spatial Dubin model to study the impact of environmental pollution on housing prices. We used housing price data, environmental data and other economic data from 258 cities in China from 2008 to 2019. The city data mainly comes from the city statistical yearbook. Environmental data mainly comes from environmental monitoring websites. This paper found that the increase in sulfur dioxide and nitrogen dioxide emissions will significantly reduce prices, while the increase in industrial wastewater emissions has no significant impact on housing prices. In addition, we also investigated the impact of surrounding cities on local prices. The increase in industrial wastewater discharge in surrounding cities has no significant impact on local housing prices, while the increase in environmental gas emissions has no significant impact on local housing prices. Finally, if the residents are assumed to be healthy producers, and the residents' demand-supply curve for health is transformed, it indicates that a place with a good economy in this area is often willing to pay more to maintain their health, or enjoy better medical care, or move to an area with lower air pollution levels. The conclusion of this article is that reducing the level of air pollution plays an important role in increasing the attractiveness of the city and thereby increasing housing prices. Therefore, if government policymakers want to increase the attractiveness of the city and promote economic development, they can start with improving the air quality in the city.

Do Vibrant Places Promote Active Living? Analyzing Local Vibrancy, Running Activity, and Real Estate Prices in Beijing

Although extensive research has investigated urban vibrancy as a critical indicator for spatial planning, urban design, and economic development, the unclear relationship between local vibrancy and active living needs to be clarified and requires more in-depth analysis. This study localizes urban vibrancy at both hyper-local and neighborhood scales by integrating high-resolution, large-scale, and heterogeneous urban datasets and analyzing interactions among variables representing vibrancy's environmental, economic, and social aspects. We utilize publicly available urban open data, Points of Interest requested from API, and leisure running trajectories acquired through data mining to investigate the spatial distribution of various vibrancy indicators and how they interact with physical activity at the local scale. Based on these variables, we then construct linear regression models and Geographically Weighted Regression (GWR) models to test and estimate how local vibrancy and physical activity relate to residential real estate characteristics. The results reveal the strong impact of urban form on local vibrancy but not physical activeness. At the neighborhood level, all vibrancy factors are statistically significant to local residential real estate prices but with different interactions based on location. Our study highlights the importance of accounting for locality and different physical, environmental, social, and economic factors when analyzing and interpreting urban vibrancy at a granular scale within a city.

Estimating the effects of crime maps on house prices using an (Un)natural experiment: A study protocol.

Street-level crime maps are publicly available online in England and Wales. However, there was initial resistance to the publication of such fine-grained crime statistics, which can lower house prices and increase insurance premiums in high crime neighbourhoods. Identifying the causal effect of public crime statistics is difficult since crime statistics generally mirror actual crime. To address this question empirically, we would ideally experiment and introduce a source of random variation in the crime statistics. For instance, we could randomly increase or decrease the number of offences displayed in crime statistics and measure their effects on local house prices. For obvious reasons, we cannot pursue this research design. However, street-level crime maps contain intentional errors, which are the product of a geomasking algorithm designed to mask the location of crimes and protect the identity of victims. This project leverages features associated with the geomasking algorithm to estimate the effect of public crime statistics on house prices.

The effect of input factor and optimization of input factor of shallot farm

The low competitiveness of local shallots is caused by the high cost of production, especially for the cost of seeds and labour. The high cost of production causes local selling price is higher when compared to the price of imported shallots. Increasing the competitiveness of shallots need to be done so that the local shallot are competitive in the market. The strategy to increase competitiveness can be through increasing price efficiency (allocative). Actually, the efficiency of shallot farming prices in several production centres has not been efficient. Price efficiency can be achieved by minimizing costs at a certain level of output. The purpose of this study was to analyse the factors that influence the production of shallots and the level of optimal use of inputs in shallot production. The research was carried out in Majalengka sub-district, Majalengka district, West Java in October 2021. The research method used is the survey method. The data used consists of primary data and secondary data. Primary data is obtained from sample farmers, farmer samples are taken at simple random sampling. Data analysis used: The production function of Cobb Douglas (to analyse the factors that affect the production of shallots) and the MPV equal to MC equation (to determine the optimal use of inputs). The results showed: The factors that significantly affect the production of shallots are land and seeds. The use of land and seeds has not been efficient because the land cultivated is relatively narrow and the use of seeds is still below the recommended dose. The optimal use of shallot seeds is 1,187.36 kg/ha. The use of fertilizers (ZA, urea) and pesticides should be reduced because the increasing those input factors will reduce the shallot production.

An Economic Study: Date Palm Farmers in Al Ahsa Oasis-Kingdom of Saudi Arabia

The study mainly aimed to discover the factors impacting the production and profits of date palm farmers in Al Ahsa Oasis in Kingdom of Saudi Arabia for seasons 2020/2021. The study's secondary goals are represented in studying the social characteristics of date palm farmers, and the most important factors impacting the production and profits of date palm farmers in Ah Ahsa Oasis, in addition to identifying the obstacles faced by farmers. The study relied mainly on the preliminary information collected through questionnaires, and secondary information collected from different sources relevant to the research subject. Data analysis was conducted through descriptive statistics for economic and social variables, regression analysis, and Likert scale. Study results showed that farmers aged from 51 to 61 are the majority with 37%, most of whom are married with 95.4%. They have more than 10 years of experience with 81.82%, and their income is around 10000 riyals as those represent a percentage of 48.86%. The regression analysis has also showed that the production cost and the farm's area have a positive and significant effect on production quantities. The most important obstacles faced by farmers are the low productivity, the increase of damage date percentage, and low prices. The study recommends using modern technologies, hiring skilled labor that may increase profits, and encouraging exportation in order to raise local prices.

Combined Cycle, Heat Pump, and Thermal Storage Integration: Techno-Economic Sensitivity to Market and Climatic Conditions Based on a European and United States Assessment

Abstract The integration of a heat pump (HP) with a combined cycle gas turbine (CCGT) to control the inlet air temperature is a promising technology to meet the requirements imposed by the current electricity systems in terms of efficiency and flexibility. If the HP is coupled with a thermal energy storage (TES) in an inlet conditioning unit (ICU), it can be exploited in different modes to enhance the off-design CCGT's efficiency or to boost the power output at full load. Furthermore, fuel-saving would be reflected in avoided emissions. The optimal sizing of the ICU, as well as an accurate estimation of the benefits, is a complex problem influenced by several factors such as the local climate and electricity market prices. This paper aims to systematically investigate, utilizing a mixed integer linear programming (MILP) model for optimal dispatch, the feasibility of an ICU integration in different scenarios (EU and US). Different electricity markets have been analyzed and classified according to the parameters describing the average and variability of prices, the interdependency with the gas market, the ambient temperature, or the local carbon pricing policy. The most favorable conditions are identified and the dependency of the optimal ICU sizing on the climate and the electricity market is highlighted. This paper provides information for a first viability assessment: the concept appears to be highly profitable in hot regions with high price variability. Additionally, even in less profitable conditions (i.e., stable low prices in a cold climate), the system increases operating hours and reduces economic losses.

Causality Between Energy Consumption and Economic Growth: The Case of Kuwait

The causality relationship between energy consumption and economic growth for Kuwait was investigated in this study, and the impact of increasing local energy prices on Kuwait’s economic growth was examined. Our methodology relied on statistical analyses to study the causality trends between various factors such as GDP; annual oil production; oil-reserves depletion; annual energy consumption; and CO2 annual emission, to formulate a hypothesis that determine the actual causality relationship between GPD and energy consumption without having to use the already-established statistical methods. Results showed no solid foundation to support the application of growth or conservation hypothesis. Results support the neutrality hypothesis which specifies no causality relationship between energy consumption and economic growth (GDP), especially from the year 2007/2008 and beyond, which allows for adopting stricter local-energy prices with no effect on the overall economic growth of the country. Results showed, however, a close relationship between oil exports (sales) and total GDP for Kuwait. The difference between total GDP and oil GDP exactly equals the non-oil related economic growth contribution to the country’s economy. The findings of this study provide reliable and suitable basis for policymaking not only in Kuwait, but also in other single-source oil-producing countries such as GCC countries.

The cost of healthy versus current diets in the Netherlands for households with a low, middle and high education

The cost of food is an important driver of food choice and most evidence suggests that healthier diets are more costly than less healthy diets. However, current attempts to model the cost of healthy and current diets do not take into account the variation in diets or food prices. We calculated the differential cost between healthy and current diets for households with a low, medium and high education in the Netherlands using the DIETCOST program. The DIETCOST program accounts for variations in dietary patterns and allows for the calculation of the distribution of the cost of bi-weekly healthy and current household diets. Data from the Dutch National Food Consumption Survey 2012–2016 was used to construct commonly consumed food lists for the population as a whole and for households with a low, medium and high education and linked to a local food price database. The average cost of current household diets was €211/fortnight (SD 8.9) and the healthy household diet was on average €50 (24%) more expensive. For households with a low, medium and high education, healthy diets were on average 10% (€17), 26% (€50) and 36% (€72) more expensive compared to current diets, respectively. All healthy diets could be classified as affordable (i.e. requiring less than 30% of the average disposable income) as diets required around 20% of the income. To conclude, while healthy diets were found to be affordable, we found that these were more expensive than current diets, especially for those with a higher educational level. This suggests that individuals will need to spend more money on food if they aim to adhere to dietary guidelines under the assumption that they will minimally adjust their diet. Bridging the gap between the cost of healthy and less healthy foods could be an important strategy for improving population diets.

E-Carsharing siting and sizing DLMP-based under demand uncertainty

Electric vehicle (EV) sales and shared mobility are increasing worldwide. Despite its challenges, e-carsharing has an opportunity to still profit in periods of low rental demand compared to traditional carsharing. The purpose of this paper is to assess the profitability of an e–carsharing company based on distribution local marginal price (DLMP) and vehicle-to-grid (V2G) that cooperates with the distribution system operator (DSO) through a two-stage stochastic model. The AC optimal power flow (ACOPF) is modeled using second-order cone programming (SOCP) linearized by the global polyhedral approximation. The IEEE 33 bus test system and a real Kernel distribution for the EV rental demands are used in four planning cases in the GAMS environment. The results indicate that the proposed methodology does not affect EV user satisfaction. Moreover, the planning disregarding the power grid perspective is the most profitable, but the operation may not be possible in real applications due to the high-power flows via V2G. Finally, the e–carsharing planning considering the DSO perspective increased the charging cost by 1.66 % but also reduced the DLMP peak, losses, and peak demand by 2.5 %, 1.5 %, and 5.1 %, respectively. One important conclusion is that the technical benefits brought to the DSO by the e–carsharing company could be turned into services and advantages for both agents, increasing profit and mitigating negative impacts, such as higher operational costs.

ANALISIS PERBANDINGAN HARGA SATUAN PEKERJAAN DENGAN METODE SNI, BOW DAN HARGA WILAYAH I KABUPATEN CIAMIS

One of the important things in activities to get the necessary cost calculations for development is to make a Budget Plan (RAB). Calculation analysis is needed to get a budget plan that is accurate and close to the actual budget in implementation, as well as a guide for owners in providing funds. In the analysis, it must be made in detail in order to obtain optimal calculation results, one of which is the analysis of the budget plan with three case study methods for making simple residential houses. The purpose of this study was to determine the calculation of the budget with the method of SNI, BOW and Regional Price I Ciamis Regency and the most economical method of the three methods. In this study, three analyzes were carried out, namely BOW (Burgerlije Openbare Werken) analysis, 2002 SNI and Price analysis for Region I Ciamis Regency, all of which used the reference price of materials, the price of labor wages and the same volume of work, namely in related manufacturing. From the research results obtained: Budget Plan based on BOW analysis of Rp. 16,076,465.00. The Budget Plan based on the 2002 SNI analysis is Rp. 14,305,678.00. Budget plan based on Local Area Price analysis of Rp. 12,406,295.00. Of the three analyzes the lowest price is to use the price analysis of Region I Ciamis Regency (Local Price Standards in 2020) Indonesia.

Effects of Public Transport Accessibility and Property Attributes on Housing Prices in Polycentric Beijing

The public transit system is often developed in tandem with urban growth, bringing improved accessibility and raising housing prices around stations. The impact of public transport accessibility on housing prices demand in-depth empirical studies to understand the underlying factors. The confounding influence of polycentric cities, contrasting with monocentric ones, deserves more attention. We studied the effects of metro and bus accessibility on housing prices along metro lines 6, 7, 9 and 14 in Beijing under the polycentric scenario. Other property attributes, including building features, location characteristics and neighborhood amenities, served as explanatory variables. Ordinary least squares (OLS) and geographically weighted regression (GWR) were used to build the global (whole-study area) and local hedonic price models, respectively. The results indicated that GWR performed better than OLS in predicting the effects of public transport accessibility on housing prices. Residential properties with access to more metro lines and stations and bus stops were associated with higher housing prices, with metro stations exerting more effects. The premiums of monocentric and polycentric models showed similar spatial patterns. In polycentric Beijing, the premiums of metro accessibility were higher in the eastern part, and the effect of bus accessibility showed circular distribution. Beijing could be regarded as a monocentric city on a global scale, but the influence of subcenters should be considered in a local polycentric regression model. The findings can inform urban planning concerning land use and public transport provision in Beijing and selecting research models in cognate studies.

Identification and correction of ratchet effect of residential land price: empirical study on urban agglomeration in China

ABSTRACT This paper theoretically analyses the mechanism of the ratchet effect of land finance and adaptive expectations on residential land prices and discuss the distort factors and spatial characteristics of residential land price in the Yangtze River Delta urban agglomeration (YRDUA) from 2008 to 2018. It is found that:(1) Land finance and adaptive expectations significantly drive the long-term growth of residential land prices and maintain the ratchet effect under the interaction. (2) There are significant spatial spillover benefits of residential land prices, and land finance and adaptive expectations not only drive the increase of local residential land prices but also have significant positive benefits on residential land prices in neighbouring areas. (3) Land price distortion is significant in municipalities directly under the central government and provincial capitals. However, residential land prices in cities farther away from large cities are lower than their reasonable values, and the distortion correction coefficient shows a spatially graded distribution spreading from large cities to the periphery. Land finance and adaptive expectations do not make residential land prices in all cities higher than their reasonable values. The above findings have some theoretical and policy implications for optimizing land administration.

Energy and monetary efficiencies at the different altitudinal agroecosystems in central Himalaya, India

Himalayas with diverse topographical and ecological zones sustain diverse agroecosystems. Differences in precipitation regimes, cropping systems, land-use systems and availability of resources significantly affect energy flow within agroecosystems (AGEs) of the region. Thus, the present study was aimed to evaluate the energy use pattern and economic profitability of different sized agroecosystems (small, medium and large) along the altitudinal gradient [very low altitude (VLA), low altitude (LA), mid altitude (MA) and high altitude (HA)] of Central Himalaya, India. The sampling was carried out following random stratified design and total 108 agroecosystems (4 altitudes× 3 sizes × 3 replicates × 3 seasons) were assessed. Data collected on quantities of agricultural inputs and outputs were converted to energy values using standard energetic constants and monetary values on the basis of local market price. Low altitude agroecosystems predominantly support cereal + pulse based cropping systems while, high altitudes favour cash crop cultivation (vegetables). Significant variation (P < 0.05) in total input and output energy was observed seasonally, while differences were insignificant across sizes and altitudes. Irrespective of the sizes and seasons, farmyard manure (organic fertilizer) contributed major share of total energy inputs across all altitudes in the order: HA AGEs (66.7 %) > MA AGEs (66.1 %) > VLA AGEs (62.6 %) > LA AGEs (52.1 %). The share of non-renewable energy inputs (inorganic fertilizers and fuel) declined along altitudinal gradient as: LA (31.1 %) > VLA (26.9 %) > MA (12.5 %) > HA (11.8 %). Seasonally, highest net energy was recorded during rainy season (92286 M J ha−1 yr−1) followed by summer (68906 M J ha−1 yr−1) and winter (18686 M J ha−1 yr−1). The economic yield significantly increased with increasing altitude and was recorded maximum for large sized agroecosystems. Energy use efficiency (EUE) differed distinctly (P < 0.05) across seasons and was recorded maximum during rainy season (8) while, across sizes and altitudes it did not vary significantly. EUE did not reflect any definite pattern along altitudinal gradient [HA AGEs (3.84) > VLA AGEs (3.81) > LA AGEs (3.56) > MA AGEs (3.01)]. Benefit-cost ratios (BCR) differed significantly (P < 0.05) along altitudes and was maximum at VLA AGEs (5.27) however, differences were insignificant across sizes and seasons. From present study, it can be concluded that season and altitude had significant impact on the energetics and economic flow of the agroecosystems while, no marked differences were observed for size classes. High altitude agroecosystems were energetically efficient while, monetary wise very low altitude systems.

A hybrid electricity pricing mechanism for joint system optimization and social acceptance within energy communities

This article presents a framework for local electricity pricing mechanisms for households designed for social acceptance. The optimization goal of the mechanisms is to flatten the neighborhood electricity profile. The motivation and need for such mechanisms result from the expectation that the energy transition leads to high peaks in the distribution grid, both in electricity consumption and renewable generation, posing a significant challenge to these grids.Following the literature, quadratic cost functions have the potential to achieve the envisioned system optimization. However, their drawback is that consumers find the resulting pricing mechanisms too complicated and are generally not willing to participate in systems offering such prices. In contrast, the simpler pricing mechanisms currently used in practice are socially accepted. However, these mechanisms lack sufficient incentive to reduce electricity peaks in the distribution grids.Our approach is to combine these concepts in a hybrid pricing mechanism for local energy communities, using a piecewise linear cost function, that approximates a quadratic function. The resulting pricing mechanism is evaluated in a field test, and, based on the feedback of participating consumers and other criteria defined in literature, we can conclude that the proposed mechanism is socially accepted.In the implementation of this hybrid pricing mechanism, its performance can be improved such that it obtains results comparable to those of quadratic cost functions. Based on these findings, a detailed numerical evaluation, and the results from the field test, we conclude that the presented pricing mechanism has the potential for being used in practice.

Inventory Management with Advance Supply Contracts Across Multiple Replenishment Periods

In this paper, we study optimal procurement policies with advance contracting option over a finite multi-period horizon for a seasonal product. In this setting, each period is defined by the time between two consecutive inventory replenishment stages where demand is not stationary across periods. Demand for the product in each period is stochastic whose probabilistic distribution is a function of the market signal received right before the beginning of the selling season. The firm receives price discounts by making quantity contracts in advance of the selling season and thus, before the realization of the market signal. Replenishment costs vary across periods during the selling season. We investigate optimal combination of advance contracting and expedited replenishment policies using stochastic dynamic programming. Our research is primarily motivated by applications in the cruise line industry where contracts are made before the final number of bookings is realized and additional purchases can be made at ports of call with varying local prices. Our results show that optimal replenishment policies follow order-up-to policies and there is a unique advance contract amount that minimizes the expected costs over the planning horizon. We provide a numerical sensitivity analysis to investigate the effects of replenishment prices, demand volatility, and disparity between periods in terms of demand on the advance contract amount, replenishments from the spot markets, service levels, and the overall expected cost.

Exchange rate pass‐through to consumer prices in India – nonlinear evidence from a smooth transition model

AbstractUsing a backward‐looking Philips curve framework and a Logistic Smooth Transition Regression (STR) model, this article examined the exchange rate pass‐through (ERPT) to final consumer prices in the case of India. Specifically, the nonlinearity of ERPT has been investigated with respect to the level of economic activity and the rate of inflation by considering two alternative measures of exchange rate. For the first transition variable, results are markedly different between high and low‐activity regimes and signify the favourable impact of economic activity on the extent of pass‐through. In the short run, 1% exchange rate appreciation would decrease the price level by 0.244% when the economy is in a low‐activity regime; however, the same appreciation increases the price level by 0.485% when there is a boom in the economy. In the long run, ERPT in the low‐activity regime is −0.358, and in the high‐activity regime, it is 0.039. In both regimes, pass‐through coefficients differ from zero and one, implying that neither local currency pricing nor producer currency pricing characterizes the ERPT mechanism. The impact of other important determinants of inflation is also well according to theoretical expectations. Finally, for the rate of inflation, we did not report any evidence favouring the Taylor hypothesis in the case of India.

Electricity retail market and accountability-based strategic bidding model with short-term energy storage considering the uncertainty of consumer demand response

Electricity retailers participate in electricity markets as intermediaries between wholesale and retail markets. They acquire energy on the wholesale side by participating in next-day markets and the pool of power. On the retail side, they make contracts with consumers in order to meet their energy demand at a fixed price for a set period of time –generally a year. To maximize profit in planning, a retailer must choose the best strategy, which should be able to reduce the cost of purchasing energy in the wholesale market while simultaneously determining the best selling price for consumers. Customers may choose a different retailer if the selling price is too high, and the retailer may take a loss if the price is too low. One of the issues that complicate retailers’ decision is the uncertain demand response parameters that affect profit. This paper contributes with a strategic bidding model for planning with short-term energy storage while considering the uncertainty of consumer demand response and load response programs simultaneously. GAMS and MATLAB are implemented in this research to analyze the data and review the results, which indicate that an increase in profit is expected to be greater than when the retailer uses only a load response program or a short-term energy storage system. As uncertainty grows, so does local price sensitivity, and, as a result, so does the predicted rate of profit. Profits from participatory reservation, energy, and regulation markets increase in the robust model, while profits from the common participatory market decrease, i.e., according to this study, which looked at both probabilistic and robust models of retail market participation. When a robust model is used, the overall profit is higher than that obtained from a probabilistic model.

Competitiveness and Government Policy Implications of corn commodities in Belu Regency

Corn is a staple food for farmers in East Nusa Tenggara, especially Belu regency. The cultivation of corn commodities is still limited to meet the food needs of farmers’s households and not yet fully commercialized by farmers. The study is aimed at examining: 1). profitability of corn farming activities; 2). Corn competitiveness; 3). policy impact (market distortion) on input and output of corn commodities. The sampling technique was carried out by purposive sampling for area samples and farmer samples. The data obtained was analyzed using the Policy Analysis Matrix (PAM) method. The results showed that the corn commodity in Belu regency reached high competitiveness. The NPCI value &lt; 1 indicates that government policies on inputs increases the competitiveness of corn commodities. The NPCO value &lt; 1 indicated that the current condition of local corn prices was lower than the social price which means it relatively does not provide maximum incentives for the development of corn farming in Belu regency. Whereas the influence of government policy instruments which is currently applied in the input-output market has a disincentive effect on the development of corn in Belu regency, because the added value obtained by farmers (private) was lower than what should be accepted (social), which is only about 78% and 57%. This was reflected in the EPC value of hybrid corn and local corn, which is 0.78 0.57 respectively.