Reassessing Inflation in South Korea: An Alternative Approach Using the Engel Curve

شاخص قیمت مصرف کننده (CPI) و شاخص قیمت تولید کننده (PPI)، دارای مفاهیم مرتبطی هستند. روابط بین این دو ممکن است از نوع علی و یا غیر علی باشد. این پژوهش به بررسی رابطه علیت میان شاخص قیمت مصرف کننده(CPI) با شاخص قیمت تولیدکننده(PPI) طی دوره 1378:01 تا 1390:01 در ایران می پردازد. نتایج بدست آمده از روش علیت گرنجر نشان می دهد که PPI علیت گرنجری CPI بوده است. همچنین نتایج مدل تصحیح خطا نیز نتایج این آزمون را مورد تایید قرار می دهد.. نتایج مطالعه گویای این است که در اقتصاد ایران، عوامل سمت تقاضا نقش مهم تری نسبت به عوامل طرف عرضه دارا می باشند، گر چه دو طرف عرضه و تقاضا بر روند تورم داخلی که توسط CPI اندازه گیری موثر می باشند.

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.

Based on the fluctuation characteristics of residents’ disposable income and CPI (Consumer Price Index) in different periods, this article introduces a nonlinear threshold cointegration theory, establishes a TVECM (Threshold Vector Error Correction Model) of the residents’ disposable income and CPI. We propose an algorithm to obtain maximum likelihood estimation under the condition of cointegration vector and threshold value which are unknown and then propose a SupLM test for the presence of a threshold. The asymptotic distribution of the SupLM statistic is analyzed, and it appears to depend on the moment functionals, so tabulated critical values are unavailable. We discuss how the residual bootstrap can be used to calculate asymptotic critical values and p values, investigate the size and power of the SupLM test using Monte Carlo simulation, and find that the test works quite well. In the empirical section, we apply our methods to test and estimate the TVECM of residents’ disposable income and CPI. According to the experimental results, the causal relationship between residents’ disposable income and CPI under different mechanisms is tested and compared with the test results under the linear cointegration hypothesis. The empirical results show that the disposable income of residents and CPI belong to a two‐mechanism nonlinear threshold cointegration system. When the deviation from the equilibrium state exceeds the threshold value, the system may adjust to the equilibrium state, and the adjustment speed of CPI shall be faster than that of the residents’ disposable income.

This study aimed to identify the correlation between global climate phenomena, such as the ENSO, and South Korea’s Consumer Price Index (CPI) for a climate-sustainable economy. South Korea’s CPI has shown a linear upward trend, prompting a trend analysis and the subsequent removal of the linear trend for further examination. The correlation analysis identified statistically significant cases under the study’s criteria, with the Southern Oscillation Index (SOI) displaying the highest contribution and sensitivity. When comparing general correlations, the strongest relationship was observed with a 27-month lag. The Granger Causality Test, however, revealed causality with a 9-month lag between the CPI and El Niño–Southern Oscillation (ENSO) indices. This indicates the feasibility of separate analyses for long-term (27 months) and short-term (9 months) impacts. The correlation analysis confirmed that the ENSO contributes to explainable variations in the CPI, suggesting that CPI fluctuations could be predicted based on ENSO indices. Utilizing ARIMA models, the study compared predictions using only the CPI’s time series against an ARIMAX model that incorporated SOI and MEI as exogenous variables with a 9-month lag. Using the ARIMA model, this study compared predictions based solely on the time series of CPI with the ARIMAX model, which incorporated SOI and MEI as exogenous variables with a 9-month lag. Furthermore, to investigate nonlinear teleconnections, the neural network model LSTM was applied for comparison. The analysis results confirmed that the model reflecting nonlinear teleconnections provided more accurate predictions. These findings demonstrate that global climate phenomena can significantly influence South Korea’s CPI and provide experimental evidence supporting the existence of nonlinear teleconnections. This study highlights the meaningful correlations between climate indices and CPI, suggesting that climate variability affects not only weather conditions but also economic factors in a country.

‘Dog Days’ Full Employment without Depreciation: Can It Be Done?

The scientific article contains a review of domestic and foreign literature on the issues of ensuring growth in the gross domestic product, pricing in the conditions of agricultural production, and import substitution. Data from the official website of the Federal State Statistics Service on the dynamics of the consumer price index and the level of gross domestic product in the period from 2017 to 2023 are presented. Statistical data on the dynamics of the level of the consumer price index showed significant changes both in the direction of increasing consumer prices and in the direction of their decrease. Thus, in 2022, a significant increase in consumer prices amounted to 3.55 percent, and in 2023, there was a decrease in consumer prices by 4.52 percent. The growth (decrease) rate of the consumer price index and gross domestic product was determined, a decrease in the gross domestic product in 2020 by 1.7 percent and a decrease in the consumer price index in 2019 by 1.2 percent were identified, and in 2023 there was a decrease of 4 percent. It is noted that the decline in gross domestic product in 2020 is associated with the COVID-19 pandemic. In order to identify the relationship between the level of gross domestic product and the consumer price index, the value of the correlation coefficient was determined. The positive value of the correlation coefficient recorded a direct relationship between the volume of gross domestic product and the consumer price index. A correlation coefficient value of 0.9 indicates a close relationship between the volume of gross domestic product and the consumer price index. Thus, the results of theoretical studies have been confirmed that the volume of gross domestic product is significantly influenced by the level of consumer prices.

Appropriateness of Inflation Indices for an Open Emerging Economy

This research investigates the profound impact of irregular commodity price changes during unusual circumstances, particularly focusing on the COVID-19 pandemic. The research stems from the recognition that global events have the potential to trigger irregular and drastic changes in commodity prices. This research holds significant implications for both consumers and policymakers in navigating the complexities of global crises. The research employs the Consumer Price Index (CPI) as a crucial indicator to chart drastic changes in consumer product prices from January 2019 to September 2023. To establish a baseline, CPI data from January 2010 to December 2018 is utilized, and an Autoregressive Integrated Moving Average (ARIMA) model is employed to forecast hypothetical CPI for the target period. The comparison between forecasted and observed CPI data reveals the vast influence of the COVID-19 pandemic on consumer prices. This research explores various subcategories of CPI, emphasizing sectors such as Food and Beverage, Transportation, Housing, and Medical Care. The research found that COVID-19 leads to delays and lagging effects in certain sectors reflecting the overall increase in consumer product prices. The Medical Care CPI also exhibited the most complexity, reflecting the immediate and direct impact of the pandemic on healthcare costs.

According to an analysis done by the EPA, the costs of pollution control had forced the closing of plants employing about 20,000 people by 1976. However, other studies showed that air and water pollution control investments forced by local, state, and Federal regulation had also created 600,000 jobs. According to a study done by Chase Econometric Associates for the US Council on Environmental Quality for the period 1970--1983, Federal pollution control requirements would cause an average annual increase in the Consumer Price Index (CPI) of 0.3 to 0.4%, with the 1978 figure estimated at 0.5%. These figures are in line with those of the US Council on Wage and Price Stability which estimates that the inflationary impact of all Federal regulatory efforts adds 0.7% to the CPI. Thus, any realistic modification of Federal environmental regulations would produce no significant reduction in the overall CPI. If the inflationary impact of these requirements could be reduced by 20%, the increase in the CPI would be restrained by only 0.1%.

The Consumer Price Index (CPI) bias for New Zealand is calculated by estimating the food Engel curves for demographically similar households with the same level of CPI-deflated incomes at different points in time. For the 17 years from 1984 to 2001 the bias in the New Zealand CPI as a cost-of-living index averaged over 1% annually. This bias is similar to estimates for the US when the same method is used over a similar era. Thus, the claim of some statistical agencies that bias in their own CPI is less than the widely discussed bias in the US may not be supported. The estimated CPI bias justifies the initial choice of inflation target for the Reserve Bank of New Zealand but not the recent raising of the target.

This paper aims to study the relationship between producer price index (PPI) and consumer price index (CPI), as well as between components of producer prices and components of consumer prices in Azerbaijan by using monthly data covering the period from March 2004 to June 2023. Applying wavelet analysis approach, I find that there is a mixed relationship between CPI and PPI, and co-movement is observed mainly at medium and low frequencies. The results reveal that although there is a weak co-movement between aggregate PPI and CPI, a significant and strong relationship exists between food PPI and aggregate CPI, as well as between food PPI and food CPI. Additionally, producer prices of agricultural products demonstrates comovement with consumer prices in certain periods. In terms of lead-lag relationship, producer prices lead consumer prices. Although wavelet methodology does not necessarily determine causality, this study provides insights for policymakers about the direction of possible causality between producer prices and consumer prices.

Oil prices (OP) may play a significant role in determining inflation in any oil-importing economy and could have an asymmetrical effect as well. Thus, this paper aims to explore the asymmetric influence of OP, broad money supply (BMS), and domestic debt (DD) on the Consumer Price Index (CPI) in the oil-importing economy of Pakistan using the nonlinear autoregressive distributive lag (NARDL) methodology on an annual sample from 1980 to 2021. The long-run results show that increasing OP and BMS have a positive effect on CPI. Similarly, decreasing OP and BMS have a positive effect on CPI. So, increasing OP and BMS is raising price levels, and decreasing OP and BMS is reducing price levels. OP has a positive and symmetrical effect on CPI. However, the BMS has a positive but asymmetrical effect on CPI. Furthermore, the effect of decreasing BMS is found greater than increasing BMS. Moreover, the effect of DD on CPI is also found asymmetrical. The increasing DD has a positive effect, and decreasing DD has a negative effect on CPI. The most of short-run results follow the long-run results. However, energy usage shows a negative effect on CPI in the short run, which is insignificant in the long-run results. This study recommends controlling the money supply and oil prices to reduce consumer prices.

Historically there are two aggregate measures of prices in the United States, the Wholesale Price Index (WPI) which measures the price of goods at the first commercial transaction in the economy and the Consumer Price Index (CPI) which measures the price of goods and services at the retail level. The general public and some economists commonly believe that current changes in the WPI are followed automatically by future changes in the CPI. This view depends on two factors: The fact that the transaction at the wholesale level occurs before the retail sale and that people believe that all wholesale price changes are transmitted through the distribution system and are contained in the final retail price. There is some support, however, for the opposite viewpoint, that is, that there is no statistical relationship between changes in the WPI and the CPI. The basis for this view is that the two indexes are different samples from different universes of prices and that there is no a priori reason to assume that changes in one universe will occur in or be transmitted to the other. Some support for this second view, the contents of the indexes, and their relationship to each other are discussed in Bechter and Pickett [2]. While both of these views have been expressed, neither has been supported by an examination of the data by thorough statistical analysis. It is reasonable to hypothize that the relationship between changes in the WPI and CPI is described by a distributed lag model since CPI changes are expected to occur over time after and in response to WPI changes. This paper explores the hypothesis that the relationship between wholesale (producer) price changes as measured by the WPI and consumer price changes as measured by the CPI is described by the distributed lag model suggested by Solow [10]. This model assumes that the lag coefficients of the model follow a Pascal distribution. The Pascal distribution was selected for its ability to provide both a lag distribution with geometrically declining weights, the well known Koyck model, and a unimodal lag distribution where the maximum lagged effect may be in a later time period. The results of the analysis support the hypothesis that there exists a significant relationship between changes in the two indexes and the Pascal distribu-

Identifying the role of consumer and producer price index announcements in stock index futures price changes

Food price trends in South Korea through time series analysis.