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PurposeThis study aims to research how the outbreak of coronavirus disease 2019 (COVID-19) impacts the selected sector price indices in Borsa Istanbul (BIST), Turkey.Design/methodology/approachThe authors use the event study method because it is a useful method as stock prices and market instantly reflect the effect of such an unusual event. Data are retrieved from the https://www.investing.com/.FindingsThe authors find that selected sectors are impacted by the COVID-19 outbreak. The banking and transportation sectors, on the announcement of first death, were impacted negatively, while the telecommunication and food –beverage sectors were impacted positively. The transportation and banking sectors experience an obvious downturn after the spread of COVID-19, while the food–beverage and telecommunication sectors experience an obvious upturn after the spread of COVID-19. Besides, the most adversely impacted sector is banking.Originality/valueThis study bridges the research gap and adds significant insights to the existing literature. The main contribution of this study to the existing literature is the unexpected outbreak impacts on financial markets, especially on BIST. It is also expected that this study will make a significant contribution to analysts, researchers and policymakers.

This paper estimates agricultural total factor productivity (TFP) in 162 countries between 1991 and 2015 and aims to understand sources of cross-country variations in agricultural TFP levels and its growth rates. Two factors affecting agricultural TFP are analyzed in detail - imported intermediate inputs and climate. We first show that these two factors are independently important in explaining agricultural TFP - imported inputs raise agricultural TFP; and higher temperatures and rainfall shortages impede TFP growth, particularly in low-income countries (LICs). We also provide a new evidence that, within LICs, those with a higher import component of intermediate inputs seem to be more shielded from the negative impacts of weather shocks.

Exchange Rate is one of the economic indicators in the Philippines. It is the value of the nation’s currency versus the currency of another country or economic zone. This study aims to forecast the monthly Exchange Rate (y) of the Philippines from November 2018 to December 2023 using Multiple Linear Regression and Multi-Layer Feed Forward Neural Network. The researchers investigate the behaviour of each independent variables – Inflation Rate (x1), Balance of Payments (x2), Interest Rate (x3), Producer’s Price Index (x4), Export (x5), Import (x6), Money Supply (x7), and Consumer’s Price Index (x8) from Philippine Statistics Authority (PSA) starts from January 2007 up to October 2018. Multiple Linear Regression (MLR) was used to identify significant predictors among these independent variables. The Exchange Rate (y) had undergone first difference transformation. Upon running the regression analysis, it has concluded that only two independent variables are significant predictors, namely: Balance of Payments (x2) and Import (x6). Through these significant predictors, the MLR model was formulated. On the other hand, Multi-Layer Feed forward Neural Network (MFFNN) was also used to determine the forecasted values of Exchange Rate (y) for the next five years (2018-2023) given the said independent variables and obtained a model. The researchers compared the model of Multiple Linear Regression and Multi-Layer Feed Forward Neural Network by evaluating the forecasting accuracy of each method.It was concluded that Multi-Layer Feed forward Neural Network is the best fitting model for forecasting the Exchange rate (y) in the Philippines. This paper will serve as a tool of awareness for the government to forsee the trend of Exchange Rate in the Philippines on the next five years (2018-2023) for Monetary Policy making and to prevent the possible depreciation of peso vs. dollar.

A representative and unbiased fish price index is an important tool to measure price risk, as well as for production and marketing management. This paper investigates the relationship betwe...

The quantity theory of money lost much of its significance in 1980s due to the phenomenon of velocity decline and consequent instability of the money demand function; missing financial transactions and asset prices were believed to be responsible (Borio, Kennedy and Prowse, 1994; and Werner, 2012). This study, therefore, uses asset prices for Pakistan to explain the velocity decline phenomenon in a regression model as well as in Vector Error Correction Model (VECM) using quarterly data for the time period 1981Q1-2018Q2. The study finds significant role of asset price index in explaining income velocity of money with a negative effect. Moreover, the sub-sample regressions show that asset prices are helpful in explaining velocity decline phenomenon for the time period 1981-1998 and 2008-2018 but not for 1998-2008. Moreover, there are brief periods in the sample when velocity actually increased despite an overall declining trend. To explain those short term reversals in velocity trend, the study uses indicator function. Results show that the increase in velocity for brief periods is also explained by asset prices

The article considers the transformation of the money function as a consequence of the impact of dollarization on the economic development of countries in the global context. The economic substantiation of the process of dollarization of the economy, which is connected with the function of money, is proved. The influence of dollarization on the macro – and macro levels of the economy is substantiated. Approaches to methods of estimating dollarization on the economic development of the country in the context of globalization are proposed. The article defines the degree of dependence of the machine-building industry of Ukraine on the processes of dollarization of the world economy through the use of the effect of transferring the dynamics of changes in exchange rates to the price dynamics in the machine-building industry. Using the ARIMA model, the effect of transferring the exchange rate to prices for mechanical engineering products is proved. The expediency of using the ARIMA forecasting model to predict the further spread of the effect of the change in exchange rates on prices. An approach is proposed to determine the sensitivity of domestic prices for the products of engineering enterprises to changes in the exchange rate through modified elasticity coefficients. It was determined factors affecting the size of the effect of transfer of the exchange rate on domestic prices for the products of machine-building enterprises.

This paper proposes the use of a semiparametric model based on a locally weighted approach that controls for dynamic agglomeration and diffusion effects in constructing localized housing price indices. Based on residential transaction records in Singapore, we create a three-dimensional interactive heat maps that allow for better measurement and visualization of spatial variations and heterogeneity in price appreciation. The heat map captures regional variations and temporal dispersions in price appreciation rates in the business cycle. Our methodology provides high-resolution information about price dynamics that could aid individual buyers, investors, and policy makers in making objective and informed decisions.

PT Arta Boga Cemerlang merupakan distributor tunggal yang mendistribusikan produk dari sejumlah produsen ke seluruh wilayah Indonesia. Dalam menghadapi persaingan antar pelaku bisnis di era globalisasi ini, suatu perusahaan harus didukung oleh strategi dan taktik dalam melakukan tindakan bisnis. Untuk mengetahui tingkat produktivitas PT Arta Boga Cemerlang, maka perlu dilakukan pengukuran produktivitas. Pengukuran produktivitas dilakukan dengan menggunakan metode The American Productivity Center (APC) model. Model APC juga bisa melakukan pengukuran profitabilitas dan indeks perbaikan harga. Data yang diperlukan untuk analisa produktivitas ini diambil dari tahun 2014 sebagai periode dasar sampai tahun 2017. Hasil analisa pengukuran produktivitas yang telah dilakukan menunjukkan bahwa tingkat produktivitas untuk input total PT Arta Boga Cemerlang pada tahun 2017 meningkat sebesar 3,010%.Kata kunci: Analisa Produktivitas, The American Productivity Center (APC) model, Indeks Perbaikan harga, Pengukuran, periode dasar.

Classification in statistics is usually used to solve the problems of identifying to which set of categories, such as subpopulations, new observation belongs, based on a training set of data containing information (or instances) whose category membership is known. The article aims to use the Gaussian Mixture Model to model the daily closing price index over the period of 1/1/2013 to 16/8/2020 in the Kingdom of Saudi Arabia. The daily closing price index over the period declined, which might be the effect of corona virus, and the mean of the study period is about 7866.965. The closing price is the last regular deal that took place during the continuous trading period. If there are no transactions on the stock during the day, the closing price is the previous day’s closing price. The closing auction period comes after the continuous trading period (from 3 : 00 PM to 3 : 10 PM), during which investors can enter by buying and selling the stocks at this period. The experimental results show that the best mixture model is E (equal variance) with three components according to the BIC criterion. The expectation-maximization (EM) algorithm converged in 2 repetitions. The data source is from Tadawul KSA.

This paper imputes the effects of US tariffs on wages attributing variation in the import price index completely to tariffs starting with availability of the index in 1983. The average wage derived from the labor share of income and the labor force is treated as the dependent variable. Single equation error correction estimates based on the factor proportions model include energy Btu input with capital and labor. Fixed capital assets effectively imbed technology. An intensive specification based on growth theory and a labor market model are also estimated. These estimates find no imputed effects of tariffs on wages.

We document a new source of consumer price microdata. The new database allows researchers studying consumer price behaviour to access current and granular raw statistical observations. The range of observed prices fully covers goods and services of the Rosstat’s CPI sample and extends beyond it. In this paper, we pursue two objectives. First, we describe the data collection mechanism, data structure, and their access protocols, as well provide four complete illustrations of their application using open API: i) training machine models of product classification based on text labels, ii) real-time tracking of product prices, iii) estimating hedonic regressions for product groups, and iv) calculating arbitrary analytical price indices. Second, we share a set of basic skills and technologies for the benefit of researchers interested in creating their own sources of alternative data.

The aim of this study is to look for an answer to the question of “Is it possible to discuss the existence of an efficient market for the housing market in Turkey?”. It was observed that relatively low housing (mortgage) interest rates were accompanied by price rigidity. Accordingly, in the formation of the housing market definition from the Central Bank (CBRT) database; an empirical analysis was made using the Residential Property Price Index for New Dwellings (NRPPI), the Residential Property Price Index for Existing Dwellings (ERPPI), the Residential Property Price Index (RPPI) and the Hedonic House Price Index (HHPI). The data range for the first three indices is between 1/2010 and 1/2020. Hedonic housing price index data range is between 1/2011 and 1/2020. Unit root tests were used to test the Random Walk Theory, which shows the characteristic condition of the housing market. The results from the study show that above average sustainable returns cannot be obtained from the housing market, as a result the market is poorly efficient. At the same time the housing market in Turkey, the rigidity of prices found along with excess supply situation is worrisome. Therefore, it is necessary to prevent all kinds of manipulative news that may occur in the housing market by the regulatory and supervisory institutions.

The compilation of commercial property price indices (CPPIs) is challenging. Policymakers urge for timely, reliable and comprehensive data. In Germany, lack of data prevents the calculation of official figures by the national statistical authority. Different applications of price indices need different definitions of commercial real estate. CPPIs according to these definitions are constructed on the basis of existing data for 127 German towns and cities (that cover about one-third of German population). The overall price developments revealed by the various indices are rather similar in terms of central time series characteristics, while differences in detail can be explained by their specific compositions. Price increases for all definitions have been strongest in the seven largest cities. The definitions tend to lead to more marked differences for medium-sized towns.

Using the gravity model, this article investigates the determinants of tourist inflow to India. Several origin–destination (O-D) linked factors, such as Gross Domestic Product, Price index, Exchang...

The directions of statistical analysis of the country’s foreign trade processes are considered in the article. Possibilities of statistical methods for studying the state and the main trends that have developed in this area are highlighted. The conclusions about the intensity of the dynamics of the trade balance indicators are generalized. The processes of the outstripping development of imports over exports are highlighted. The dynamics of the balance of export-import operations is analyzed and trends of its deterioration are demonstrated. The degree of coverage of imports by exports and the processes of formation of the trade balance deficit are investigated in time. The directions of development of characteristics of the balance of foreign trade operations are studied. High levels of export and import dependence of the country have been demonstrated, which leads to vulnerability to external shocks and instability in the world. The results of the analysis of the structure and structural shifts in the trade of Ukraine with the countries of the Visegrad Four are presented. The emphasis is made on the prospects of interrelations with this group of countries from the point of view of using their experience in preparing for accession to the EU. The article demonstrates more intensive changes in the geographical structure of exports than imports and highlights the tendencies towards an increase in the role of Poland and a decrease in Hungary in the export-import operations of the Visegrad Four with Ukraine. The processes of changing the terms of trade have been investigated in terms of changes in export and import prices and in terms of changes in the physical volume of exports and imports on the example of a group of dairy products, which are widely represented among both export and import goods of Ukraine. The index method was used to analyze the absolute and relative impact of changes in prices and the physical volume of exports and imports of a number of dairy products on the value of exports and imports. Changes in the terms of trade are highlighted by constructing quantitative and price indices of the terms of trade. It was clarified that it was the sharp reduction in the physical volume of exports that contributed to the decrease in foreign exchange earnings from the export of dairy products. The necessity of measures to promote domestic goods abroad, primarily to European countries, has been substantiated. The research results can be used in foreign trade policy at the macro level.

There is some new challenges about the greenhouse gases, climate changing, and weather warming. The applying of the various Energy Policies (EPs) on production sections, is the prevalent solution that considers promotion of the renewable energies. The result is enhancement of penetration rate of the Renewable Energy Sources (RESs) in the power systems. However, till now, there are little papers that assessed the effects of EPs on the social welfare. The social welfare consists of the financial profits of the RES production company as well as the surplus welfare of subscribers. In this paper, the results of the implementation of a well–known EP as the Renewable Energy Certificate (REC) and its effect on the surplus welfare are assessed, based on the Generation Expansion Planning (GEP). In order to obtain the paper aims, the desired EP and the GEP are mixed, and a comprehensive model is presented from the perspective of an RES production company. The model is solved in the form of a Mixed Integer Non–Linear Problem (MINLP) in the GAMS optimization software using the BARON optimizer. Also, in order to reach complete solution, two scenarios as without and with the proposed EP are considered, and the results are compared with other EPs. For evaluation of the social welfare, a criteria as the Virtual Price Index (VPI) is introduced. With analysis of the results, it could be seen that the surplus welfare of the subscribers increases in the long term horizon, while it was lower than profit of the RES production companies at short terms.

This paper analyzed how economic variables affect the Chinese B-share market. For this purpose, we investigated the monthly data of major economic variables (consumer price index, imports and exports volume, money supply, real estate index and retail sales volume) and B-share price index of Shanghai and Shenzhen Exchange of China from 2009 to 2019 by employing the multivariate VAR-GARCH-BEKK model. We measured the return spillover effect between Chinese major economic variables and B-share market index from the estimation results of VAR conditional mean equation, and volatility spillover effect between the economic variables and B-share index from the estimation results of GARCH-BEKK conditional variance equation. From these results, we investigated whether there is any difference between the Shanghai and Shenzhen Exchange markets. The main findings are as follows. First, the return spillover effect does not exist in both markets except the Consumer Price Index (CPI). Second, there is the volatility spillover effect between economic variables and Shenzhen B-share market, implying that the volatility spillover effect is more important than the return spillover effect in the Chinese B-share market. Third, compared with Shanghai, the change of the Shenzhen stock market is more affected by the change of economic variables. These findings have some important policy implications. First, investors in Chinese stock market need to make good use of the information inherent in China’s economic changes to increase returns and reduce investment risks. Second, the investors should pay close attention to the overall trends of the Chinese economy and the global economy, not just to the trends of the Chinese market.

This paper aims to explore the distribution of inflation rates at the household level and estimate their determinants using the Household Budget Surveys. It derives the household level inflation rates using the democratic price index and analyzes inflation inequality and its persistency. The main contributions of the paper are as follows: (i) to determine inflation inequality by examining the distribution of household-specific inflation rates calculated by the democratic price index, (ii) to examine new dimensions of inflation inequality in Turkey by income groups and household characteristics, (iii) to estimate the micro-level determinants of household inflation rates in Turkey. Results suggest that inflation rates are lower for the rich than for the poor, and the distribution of inflation has worsened the income inequality in Turkey. This analysis provides rich information for monetary policymakers. Households have different responses to price changes or monetary policy tools because of their unique characteristics and economic conditions. Thus, we need to know how inflation rates differ at the household level in order to understand how monetary policy and inflation affect the well-being of households.

This paper aims to fill two purposes: 1) we document that housing price index between different cities have inter-correlation. This means that when the housing price in one city goes up the other city follows. However, in the case of a big city and a small city, the housing price index of small city follows the path of housing price index in the small city. 2) The housing price index is a measure of wellbeing and wealth of residents. At the onset of a pandemic, wealthy and richer people have a wealth-protective shield against the disease. We show that this is the case in the US. We document that higher housing price indexes are associated with lower confirmed case of Covid-19 and lower risks of death due to the disease.

In recent years, financial market dynamics forecasting has been a focus of economic research. To predict the price indices of stock markets, we developed a hybrid non-stationary model with Elman’s ...

Purpose This study aims to motivate the reality that experiential investigation of immiserizing growth has not been performed at large. The key objective of the study is to analyse the empirical existence of immiserizing growth in the real world. Design/methodology/approach Theory of revealed preferences has been implemented for welfare movement by using Laspeyres and Paasche quantity index and for empirical estimations, logistic regression has been applied. The study established panel data of the world’s largest trading nations, including the USA, China, France, Germany, UK, Italy, Japan, the Netherland and Canada. Annual time series data for an extensive time period covering from 1981 till 2017 have been used. Findings Findings of the Laspeyres and Paasche index reveal that out of nine countries immiserizing growth prevails in five nations and those are Italy, Canada, the Netherland, UK and Japan. The results of panel logistic regression verify the significance of terms of trade on immiserizing growth in all included countries. Separate logistic regression has also been performed on all the five countries from which Italy, Canada, the Netherland exhibit significant results. Originality/value This study is a pioneer attempt towards the concept of immiserizing growth. Considering the fact that immiserizing growth is viewed by the majority of the scholars as a theoretical notion, this study attempts to investigate analytically the existence of immiserizing growth with real data set. The impact of terms of trade deterioration on the welfare of the world’s largest trading nations has been focused on the research which is in compliance with the concept of Bhagwati (1958).

Real estate platforms provide a new source of data which has already been used as a substitute for transaction data in hedonic regression applications. This paper asks whether it is valid to do so in the established research areas of (1) willingness to pay estimation, (2) automated valuations, and (3) price index construction. It therefore compares listings and transaction data and regression results derived from them. We find that ask prices stochastically dominate sale prices, mainly because the composition of characteristics differs between the two data sets. But estimates of implicit prices also differ. As a result, willingness to pay estimates from listings data can be widely off when compared with estimates from transaction data. Listings data are not very useful to predict market values of individual houses either, as these predictions suffer from upward bias and large error variance. We find, however, that an ask price index complements a sale price index, as it is useful for nowcasting. Supplementary Information The online version contains supplementary material available at 10.1007/s00181-020-01992-3.

This paper finds that the shift from buying music as a physical product towards subscribing to music services implies a decrease of 85 percent in the price paid per song. We estimate that in 2019 the global quality adjusted value from streamed music was $76 billion compared to current revenues of $11.4 billion. Thus, the shift from consuming music in physical form towards subscribing to music services creates an enormous consumer surplus that is not recorded in GDP.

Standard cost-of-living indexes assume that preferences are homothetic, ignoring the well-established fact that tastes vary with income. This introduces systematic biases in measures of purchasing power parity across locations. I develop a framework that characterizes non-homothetic preferences across many sectors and use household-level grocery data from Nielsen to structurally estimate the model parameters. I use this model to show that cross-city price indexes vary widely across income groups. Grocery costs are 20 percent lower in a poor city relative to a wealthy city for a low-income household, but they are 20 percent higher in the poor city for a high-income household. I find that homothetic price indexes perform well in predicting the cross-city variation in prices for low- and middle-income households, but poorly for high-income households. These results suggest that using homothetic cost-of-living indexes understate the relative price level in poor locations for rich households.

Este trabalho tem como objetivo avaliar como as mudanças na estrutura produtiva chinesa impactaram os preços de bens industriais exportados pelo país entre 2001 e 2017. Para isto, considera-se o preço sendo uma variável explicativa da qualidade das exportações. Metodologicamente propõe-se calcular as margens intensiva e de qualidade de acordo com Hummels e Klenow (2005) para grupos setoriais categorizados por tipos de tecnologia (intensivas em escala, diferenciadas e baseadas em ciência). Com isso, a análise dos setores intensivos em escala, diferenciados e baseados em ciência sinaliza que há um processo virtuoso de transformação produtiva e tecnológica chinesa à medida que se observa um aumento generalizado da relevância das exportações chinesas em terceiros mercados, via margem intensiva. No entanto, a margem de qualidade das exportações, representada pelo índice de preços, encontra-se em uma posição inferior comparativamente às principais economias em termos de desenvolvimento produtivo e tecnológico.

The food-energy-water (FEW) nexus provides leeway into the lateral transmission of price volatilities within the sectors. The problem is that any inflationary price tendencies in one of the FEW sectors will have direct and indirect effect on the other. The objective of the study was to ascertain the relationship between inflation in food, energy and water, and determine whether there were spill-overs, in South Africa. Monthly consumer price indices for food, energy and water for the period spanning from January, 2002 to December, 2020, were used. Parsimonious vector autoregressive (VAR) model was used in data analysis. The study found that prior to 2013, inflation rate was higher for food relative to water and energy, respectively. After 2017, water had a higher inflation rate relative to energy and food, respectively. Furthermore, energy inflation had positive impact on both water and food inflation, whilst water inflation also had positive impact on food inflation. The study concludes that there is a nexus in the lateral inflation between food, energy and water. Recommendations include building resilience within the nexus through decoupling food and other sectors from fossil fuel-derived energy. There is need to strike a balance in biofuel and energy production policy to foster complementarities. Operational efficiencies within the sectors also need to be fostered.

This paper presents an analysis of a group of small commodity-exporting countries' price differentials relative to the US dollar. Using unrestricted self-exciting threshold autoregressive models (SETAR), we evaluate the sixteen national Consumer Price Indexes (CPI) differentials relative to the US dollar CPI. Out-of-sample forecast accuracy is estimated through calculation of mean absolute errors measures based on the monthly rolling window and recursive forecasts, and this estimation is extended to three additional models, namely a logistic smooth transition regression (LSTAR), an additive nonlinear autoregressive model (AAR), and a simple neural network model (NNET). Our preliminary results confirm the presence of some form of nonlinearity in most of the analyzed countries. The parsimonious AR(1) model does not appear to perform any worse than any nonlinear model in the rolling sample exercise. However, in terms of a longrun equilibrium driven by purchasing power parity, its validity is undermined by the results of the recursive estimates and the outcome of the Diebold-Mariano type tests, which favor generally the Heckscher commodity points theory. As a policy advice to commodity-exporting countries, we find no apparent reason to suggest commodity export price pegging as a generalized foreign exchange policy.

Vegetable production could be one of the best alternatives to break wheat-paddy rotation in the northern India. Among all the vegetables, tomato crop is a major vegetable crop after potato, chillies and peas. The study was conducted to assess the integration of tomato markets in northern India.. The present study was supported by the monthly wholesale prices of tomato data for the period of 201119 in the four national markets of India namely Amritsar, Ludhiana, Shimla and Delhi. The instability in the prices of vegetables is influenced by the number of factors such as variation in production, low price elasticity of demand, perishability and seasonality. Time series analysis of monthly prices indicated that seasonal price index does not follow any particular trend in these markets. The intra price rise (IPR), Average seasonal price variation (ASPV) and the coefficient of variation were found to be highest in Delhi and lowest for Shimla. The higher seasonal indices of all the markets were observed during the months of July-August-September-November. This was due to the early influx of monsoon which partially damaged tomato crop and led to tremendous effect on the supply and afterwards higher prices. The wholesale price series of tomato in Shimla, Delhi and Ludhiana markets were stationery at original series except Amritsar market which became stationery after first order differencing. Johensen's co-integration and Granger causality test was used to analyze the long run relationship among markets. All the markets were co-integrated with each other and were having a long run relationship. Majority of the markets were having a bidirectional price relationship and few have shown unidirectional/non-price movements.

Tender price indices (TPI) remain an optimum process for predicting tender prices. There have been several indices’ developments in the Ghanaian Building Industry (GBI) to help in cost management practices, for instance, building cost indices, and material indices among others. Notwithstanding, there are no indices for forecasting tender price at the design stage of building projects in the Ghanaian Building Industry. The motivation of this study is to develop tender price indices that would facilitate easy prediction of the initial cost of building projects. Through a thorough literature review and secondary data collection, the index was formulated using Laspeyres with Excel spreadsheet for the actual index. The variables considered include preliminaries and measured work sections which include the substructure, concrete work, reinforcement, masonry, lining/sheathing, window/door/stairs, metalwork, surface finishes, sanitary appliances/fitting and electrical supply/power light system of the Bills of Quantities. The finding of the study shows that on average there is a change in price of about 4.42 per cent within the eight-year period from 2008 to 2016. The study has developed tender price indices for the Ghanaian Building industry for the facilitation of the easy prediction of the tender prices at the initial design stage, however, the indices have an error margin of ±3. The development of these indices will serve as the basis for further development of other indices in GBI such as locational indices and value-based indices for effective cost management practices.

We examine interdependencies between agricultural, industrial, and energy commodity price indices suing data sets from more than seven centuries. To this end, we apply wavelet coherence and wavelet...

Research background: The Consumer Price Index (CPI) is a basic, commonly accepted and used measure of inflation. The index is a proxy for changes in the costs of household consumption and it assumes constant consumer utility. In practice, most statistical agencies use the Laspeyres price index to measure the CPI. The Laspeyres index does not take into account movements in the structure of consumption which may be consumers' response to price changes during a given time interval. As a consequence, the Laspeyres index can suffer from commodity substitution bias. The Fisher index is perceived as the best proxy for the COLI but it needs data on consumption from both the base and research period. As a consequence, there is a practical need to look for a proxy of the Fisher price index which does not use current expenditure shares as weights. Purpose of the article: The general purpose of the article is to present a hybrid price index, the idea of which is based on the Young and Lowe indices. The particular aim of the paper is to discuss the usefulness of its special case with weights based on correlations between prices and quantities. Methods: A theoretical background for the hybrid price index (and its geometric version) is constructed with the Lowe and Young price indices used as a starting point. In the empirical study, scanner data on milk, sugar, coffee and rice are utilized to show that the hybrid index can be a good proxy for the Fisher index, although it does not use the expenditures from the research period. Findings & Value added: The empirical and theoretical considerations con-firm the hybrid nature of the proposed index, i.e. in a special case it forms the convex combination of the Young and Lowe indices. This study points out the usefulness of the proposed price index in the CPI measurement, especially when the target index is the Fisher formula. The proposed general hybrid price index formula is a new one in the price index theory. The proposed system of weights, which is based on the correlations between prices and quantities, is a novel idea in the price index methodology.

Purpose - The purpose of this study was to analyze what influences the change in the ISSI price index. The analysis was based on the phenomena and hypotheses that occur in the capital market by examining whether there is an influence of inflation rates, interest rates, and the Dow Jones Islamic Malaysia Index as external factors, as well as profitability such as Return on Assets and Earning per Share as internal factors that have an influence on changes and fluctuations in the Sharia Stock Index.Method - The population in this study are all stocks that are encoded in the Indonesia Sharia Stock Index (ISSI) listed on the Indonesia Stock Exchange. Based on the Sharia Stock Exchange and the number of shares indexed by ISSI was 408 shares which shares were classified into 11 types of business. The study was conducted by analyzing multiple regression with t-test, significance test, F test, and classical assumption test.Result - Based on the research results of bank interest rates and the Dow Jones Islamic Malaysia Index which affect stock prices indexed as Indonesia Sharia Stock, the two variables are the external influence of the issuers of the shares. And the majority of these stock prices are strongly influenced by variable factors not examined.Implication - This research indicates that the factors that influence stock prices indexed as Islamic stocks in Indonesia, the analysis of the coefficient of determination is not significant at 0.6%, to find out other factors, other variables are needed for further research.Originality - This research is a continuation of previous research but uses different variables from previous researches, where the dependent variable is stock prices indexed as Indonesian Islamic stocks and the independent variable is the inflation rate, interest rate, and the Malaysian Islamic Dow Jones Index as factors.

Multilateral methods are increasingly being used in the computation of official price indexes such as the consumer price index (CPI). This reflects the growing use of scanner data by statistical agencies and the fact that fixed‐based or chained price comparisons perform poorly in this context. A range of multilateral approaches have been pursued by different statistical agencies. Yet, it can be shown that some of these methods, at least theoretically, could suffer from substitution bias. We investigate this as well as the drivers of chain drift. We adopt a simulation‐based approach using actual scanner data prices with the corresponding quantities being generated assuming constant elasticity of substitution (CES) preferences. We find that most methods systematically deviate from the exact CES benchmark index. This is even the case for the superlative index methods, which should not exhibit substitution bias. Interestingly, we also find significant chain drift even in the exact CES indexes. We argue this reflects life cycle pricing and particularly run‐out sales at the end of a product's life.

In this paper, we use the macro data from the first quarter of 2001 to the first quarter of 2015, through vector autoregressive (VAR) model, Granger causality analysis, impulse response function (RFI) and variance decomposition analysis of quantitative analysis methods, to research on the relationship among China’s real growth variation of gross domestic product(GDP), Money supply growth rate and consumer price index. We find that the money supply growth has impact on China’s real growth variation of GDP in short-term, but there is no long-term significant effect. Economic growth is the main factor to promote the consumer price index growth, money growth is not the main factor driving the change in the price index. China’s currency growth is affected significantly by the change of the economic growth.

Empirical findings focusing on the relationship between capital markets and macroeconomic variables are used as data sources in determining policies for the development of the conventional and Islamic financial system. The aim of this study is to investigate the existence of volatility spillover effects between foreign exchange markets and Islamic stock markets in three major emerging countries, namely India, Malaysia, and Turkey using daily data for the period 2013-2019. Volatility spillover effects are investigated using the causality-in-variance test developed by Hafner and Herwartz (2006). In order to examine the nature of the relationship between the variables, and whether it changes over time, the time-varying test statistic is estimated using rolling samples. We find evidence in favor of volatility spillovers from the Islamic stock market to the foreign exchange market only in Turkey. The time-varying test results show that the presence of volatility spillover is at least one direction between exchange rates and the Islamic stock market at specific periods. Copyright (C) 2020, Borsa Istanbul Anonim Sirketi. Production and hosting by Elsevier B.V.