• Journal of the Korean Data and Information Science Society
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• v.23 no.3
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• pp.535-542
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• 2012

The consumer price index (CPI) data is one of the important economic measurement of the country. In this article, the Autoregressive Error (ARE) model has been considered for analyzing the monthly CPI data at Seoul, Pusan, Daegu, and Gwangju Cities in Korea, In the ARE model, nine economic variables are used as the explanatory variables for the CPI data set. The nine explanatory variables are CCI (coincident composite index), won-dollar rate, producer price index, oil import price, oil import volume, international current account, import price index, unemployment rate, and amount of currency. The result showed that the monthly ARE models explained about 46-52% for describing the CPI.

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.1
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• pp.108-115
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• 1998

The objective of this study was to estimate the quantitative loss of the consumer surplus due to the tariffs on clothing imports during the WTO starting periods. For 1984-1996, the import price elasticity of the clothing was estimated from the regression of pet capita clothing imports on Per capita GNP, import price index and domestic producer price index. Then the quantitative losses of the consumer surplus in clothing were obtained from the simplified formula for 1990-1995. In spite of the decrease in textiles St clothing tariff rates, consumer costs were increasing, which was caused by the tremendous increase in clothing imports during the same period. The loss of the consumer surplus was 7131 billion wonts in 1995, which accounted for 6.4% of the total clothing expenditure.

• Asia-Pacific Journal of Business
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• v.14 no.1
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• pp.365-379
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• 2023

Purpose - Our previous study (Chang & Lee, 2023) presented observations on the recent changes in the year-on-year (YoY) Consumer Price Index (CPI) of the Republic of Korea (ROK) after the COVID-19 pandemic. The purpose of this article is to present an integrated analysis and interpretation of the recent changes in CPI and the Aggregate Import Price Index (IPI) by incorporating recent data, specifically data from September 2022 to December 2022. Design/methodology/approach - This study collected CPI (YoY) data in the ROK from January 2019 to December 2022 using e-National Indicator System provided by the ROK. Statistical analysis was employed to analyze the data. Findings - First, we confirm the extended results of the existing study by Chang and Lee (2023). Second, we demonstrate that the Aggregate IPI in ROK increased significantly in 2022 compared to 2021. We then provide an integrated interpretation on the significant increase in CPI and aggregate IPI in ROK, which complements Chang and Lee (2023) that limits their discussion to YoY CPI. Moreover, we show that the IPI of the semiconductor in ROK decreased significantly in 2022 compared to 2021. Research implications or Originality - Our results provide important insights into the recent changes in the CPI in the ROK. The results suggest that these changes can be partially attributed to various factors, such as the global supply chain disruptions resulting from the spread of the COVID-19 pandemic and the prolonged war between Russia and Ukraine, the side effect of quantitative easing by the US Federal Reserve, heat waves and droughts caused by climate change in ROK, a surge in demand following a gradual daily recovery, US-China trade conflict, etc. Our study shows statistically comprehensive results compared to the studies that limit their discussion to YoY average growth rate.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.473-478
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• 2007

We analyze competitiveness of material and component industry(MCI) of Korea, China and Japan using trade data, OECD ITCS database with HS-code system. We use unit price indices, export unit price index, import unit price index, and TOT unit price index. These indices provide quality information from trade data of value and quantity. Our results show that there are quality gaps among three countries, and that China expand development potential, and the results vary as sectors. It implies that R&D investment to improve quality of MCI products is essential and that sector-specific policy is necessary.

• The Journal of Fisheries Business Administration
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• v.29 no.2
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• pp.97-110
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• 1998

This paper tries to estimate Korea's import demand function for fisheries using cointegration analysis. The estimation function consists of one dependent variable-import quantity of fisheries(FTIW) and two independent variables-relative price(RP) between importable and domestic products and real income(GDP). As it has been empirically found out that almost all of time series of macro-variables such as GDP, price index are nonstationary, existing studies which ignore this fact need to be reexamined. Conventional econometric method can not analyze nonstationary time series in level. To perform the analysis, time series should be differenciated until stationarity is guaranteed. Unfortunately, the difference method removes the long run element of data, and so leads to difficulties of interpretation. But according to new developed econometric theory, cointegration approach could solve these problems. Therefore this paper proceeds the estimation on the basis of cointegration analysis, because the quartly variables from 1988 to 1997 used in the model is found out to be nonstationary. The estimation results show that all of the variables are statistically significant. Therefore Korea's import demand for fisheries has been strongly affected by the variation of real income and the relative price.

• Journal of Korea Port Economic Association
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• v.28 no.4
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• pp.193-207
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• 2012

The of purpose of this study is to predict export and import container volumes using a Decision Tree analysis. Factors which can influence the volume of container cargo are selected as independent variables; producer price index, consumer price index, index of export volume, index of import volume, index of industrial production, and exchange rate(won/dollar). The period of analysis is from january 2002 to December 2011 and monthly data are used. In this study, CRT(Classification and Regression Trees) algorithm is used. The main findings are summarized as followings. First, when index of export volume is larger than 152.35, monthly export volume is predicted with 858,19TEU. However, when index of export volume is between 115.90 and 152.35, monthly export volume is predicted with 716,582TEU. Second, when index of import volume is larger than 134.60, monthly import volume is predicted with 869,227TEU. However, when index of export volume is between 116.20 and 134.60, monthly import volume is predicted with 738,724TEU.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.197-204
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• 2020

Nowadays, many construction engineering and technology enterprises are evolving to find that prosperity is driven and inspired by an open economy with dynamic markets and fierce multifaceted competition. Besides brand and product uniqueness, the ability to quickly provide customers with quotes are matters of concern. Such a requirement for prompt cost estimation of construction investment projects with the use of a construction price index poses a significant challenge to contractors. This is because the nature of the construction industry is shaped by changes in domestic and foreign economic factors, socio-financial issues, and is under the influence of various micro and macro factors. This paper presents a fuzzy decision-making approach for calculating critical factors that affect the construction price index. A qualitative approach was implemented based on in-depth interviews of experts in the construction industry in Vietnam. A synthetic comparison matrix was calculated using Buckley approach. The CoA approach was applied to defuzzified the fuzzy weights of factors that affect the construction price index. The research results show that the top five critical factors affecting the construction price index in Vietnam are (1) consumer price index, (2) gross domestic product, (3) basic interest rate, (4) foreign exchange rate, and (5) total export and import.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1471-1479
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• 2017

The variability of trade price index of apartment influences on the various aspect, especially economics, social phenomenon, industry, and culture of the country. In this article, the autoregressive error (ARE) model has been considered for analyzing the monthly trading price index of apartment data. About 16 years of the monthly data have been used from September 2001 to May 2017. In the ARE model, six macroeconomic variables are used as the explanatory variables for the rade price index of apartment. The six explanatory variables are mortgage rate, oil import price index, consumer price index, KOSPI stock index, GDP, and GNI. The result has shown that trading price index of apartment explained about 76% by the mortgage rate, and KOSPI stock index.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.50
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• pp.309-331
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• 2011

Today, the world is considered to indispensable basic data in specific gravity of international trade is increasing in economic activity of every country with globalization, and trade connection index number analyzes an economy or part of trade that contribute to economic growth of a country along with other foreign trade statistics and evaluates along with this. Also, it is becoming one of big subject for economic policy person in charge and related economists I do how measure movement of amount, price and amount of materials in trade. But, about till now interest lack about trade index and trade index creation theoretical, it is actuality that export, import connection index number or similar research is not attained much into domestic and overseas from study tribe which is gone ahead. Moreover, study that try to judge and forecast stream of market applying trade connection index number is hard to find on study until now. And, in this research, there is the objective to figure out stream of Korean market change through trade business index creation that base on Korea Customs Administration export and the importation data and this is differences with several study, and at the same time, it is value of this study.

• International Area Studies Review
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• v.20 no.1
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• pp.167-181
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• 2016

In Korea, the transportation & telecommunication service industry is composed of public sector entities, such as public transportation and the postal service, and private sector entities. The public sector may be regulated in terms of pricing or is guaranteed a normal profit. Markup can be a subject for regulation. This paper is to set up the markup equation, estimate the industrial markup, and analyze the markup determinants by estimating the factor price elasticities of markup in the Transportation & Telecommunication industry. The factor price elasticities of markup were estimated to be -0.07 in wage rate, -0.45 in import price index, and -0.13 in interest rates. We suggest that import price and interest rate are major factors to be considered first of all in regulating the transportation & telecommunication industry.