Wholesale Price Index Research Articles

Life-cycle cost and financial analysis of energy components in mass housing projects – A case project in sub-urban India

Abstract Environmental concern based designs are becoming essential in urban India. Shift of population from rural to urban cities is leading to the associated burden of mass housing facilities. The paper discusses the economic feasibility of using energy conservation green components by performing their life cycle cost analysis (LCCA) in large mass housing projects. A total of six components including solar applications have been evaluated for a case project placed in Mumbai suburban location in India. LCCA is performed from the projections of Wholesale price indices and wholesale market price fluctuations of the commodities. Labour cost projections are performed from minimum wages provided by the ministry. For calculation of savings, exponential increase in electricity tariff is considered. The capital cost of energy components contributes in the range of 5–7% to the conventional built up area cost. LCCA suggests that the significant share of cost is related to maintenance, repair and replacement activities of all components. Financial analysis results suggest that the components provide a payback of 11 years at 8% discounting rate and 7 years at non discounted values. The results of this study are expected to benefit investors in mass housing projects for their financial and budgetary decision making in implementing energy efficient based design.

Asymmetric price adjustment – evidence for India

This study examines whether there exists asymmetry in the price adjustment of firms, as anticipated by Ball and Mankiw (1994), in an error correction framework. We used monthly time series data on prices of 419 commodities, which constitute 97% of commodity price basket used in the construction of wholesale price index in India. The empirical evidence indicates that the price adjustment of most of the firms exhibits strong asymmetry; shocks that increase firms' desired prices cause quicker and larger rise in prices whereas shocks that lower desired prices cause smaller or no fall in prices. Also, we identify a threshold value for each firm below which it does not allow its relative price to fall. These evidences imply that larger relative price variability can trigger inflation even in the absence of demand shocks. Moreover, the distribution of output is likely to be negatively skewed even if the demand shocks are symmetric.

Measuring core inflation in India: An asymmetric trimmed mean approach

AbstractThe paper seeks to obtain an optimal asymmetric trimmed mean-based core inflation measure in the class of trimmed mean measures when the distribution of price changes is leptokurtic and skewed to the right for any given period. Several estimators based on asymmetric trimmed mean approach are constructed and estimates generated by use of these estimators are evaluated on the basis of certain established empirical criteria. The paper also provides the method of trimmed mean expression “in terms of percentile score.” This study uses 69 monthly price indices which are constituent components of Wholesale Price Index for the period, April 1994 to April 2009, with 1993–1994 as the base year. Results of the study indicate that an optimally trimmed estimator is found when we trim 29.5% from the left-hand tail and 20.5% from the right-hand tail of the distribution of price changes.

An Econometric Analysis of Gold Prices in Turkey

Abstract This study aims to identify the factors that affect gold prices on the Turkish Gold Exchange. To that end, London Bullion Market Association's gold prices, Brent oil prices, the US dollar, the American Dow Jones Industrial Index, Wholesale Price Index, Istanbul Stock Exchange 100 Index, and monthly average time deposit interest rates were selected as the factors with possible impact on gold prices; and relevant econometric models were constructed.In the model that delivered the best results among all the models estimated by using the Engle-Granger two-step estimation procedure, London Bullion Market Association's gold prices were found to be the single and most important variable that influences the gold prices on the Istanbul Gold Exchange. Estimation of the gold prices on the Istanbul Gold Exchange in the study was done by using ARCH models. The analysis results revealed that the EGARCH(1,1) model is the best model. Using this model, it was concluded that gold prices on the Istanbul Gold Exchange are negatively influenced by the Dow Jones Industrial Index, positively influenced by London Bullion Market Association's gold prices, also positively influenced by the Wholesale Price Index, and negatively influenced by the volatility of the gold prices on the Istanbul Gold Exchange, which was estimated using ARCH models

Impact of Selected Macroeconomic Variables on Stock Market in India

Purpose of the study: The present study investigates the influence of selected macroeconomic variables in terms of international crude oil price, exchange rates, domestic gold price, real interest rates and wholesale price index on stock market indices (sensex and nifty) of India. Background: Macroeconomic variables directly or indirectly affect the stock prices because it influences strongly the stock returns by affecting the stock prices, which supports the existance of a long-run relationship between the macroeconomic variables and stock prices. Methodology: This study is based on time series monthly data collected from Reserve Bank of India database; BSE and NSE database, investing.com and yahoo, finance database for the period July 1997 to July 2015 with the application of financial econometrics. Results: The empirical results reveal that sensex and nifty reactions to shocks on crude oil prices, exchanges rates, real interest rates and whole prices indices were positive while a negative shock from sensex and nifty to real interest was noticed.

Wholesale Price Index as a Measure of Inflation with Special Reference to Basic Commodities

Wholesale Price Index as a Measure of Inflation with Special Reference to Basic Commodities

Socioeconomic classification of Indian population: A conceptual update for Biomedical Research

An update of Prasad’s socioeconomic classification (1961) of Indian population has been proposed. To handle the trend of inflation it has been linked with the revised All India Wholesale Price Index with a base year of 2003-2004. Interestingly the cutoff obtained for below poverty line corresponds to the BPL (Below Poverty Line) limit of Indian population proposed by an expert panel headed by former RBI governor. It will be the simplest form of socioeconomic classification of Indian population for conducting population and health surveys, and the classification can be updated with the release of month wise AIWPI score.

Inflation in the Indian Economy

Inflation is one of the most retarding factors of economic life and economic development. In fact, it affects almost all economic activities as well as consumption pattern of average and poor people. Since 1947, prices have continuously risen in India. It is seen that fluctuations in prices create an atmosphere of uncertainty which is not conducive to the developmental activities. In other words inflation creates uncertainty in development activities which cause a decline in the purchasing power of money. At the same time, stability in the price level is conducive for economic stability. It is quite interesting to note that what India experiences in instability in the price level are different from Keynesian view who stated that inflation occurs after the achievement of full employment level. But it is not so in India where increase in government expenditure is the major cause to inflation. Hence, the investigators attempt to analyze the inflationary trend and growth of public expenditure in India over a period of time. The fluctuation in price level is measured in terms of wholesale price index or consumer price index.

ANALYZING THE DYNAMICS OF GROSS DOMESTIC PRODUCT GROWTH. A MIXED FREQUENCY MODEL APPROACH

Frequency mismatch has been a problem in time series econometrics. Many monthly economic and financial indicators are normally aggregated to match quarterly macroeconomic series such as Gross Domestic Product when performing econometric analysis. However, temporal aggregation, although widely accepted, is prone to information loss. To address this issue, mixed frequency modelling is employed by using state space models with time-varying parameters. Quarter-on-quarter growth rate of GDP estimates are treated as monthly series with missing observation. Using Kalman filter algorithm, state space models are estimated with eleven monthly economic indicators as explanatory variables. A one-step-ahead forecast for GDP growth rates is generated and as more indicators are included in the model, the predicted values became closer to the actual data. Further evaluation revealed that among the group competing models, using Consumer Price Index (CPI), growth rates of Philippine Stock Exchange Index (PSEi), Exchange Rate, Real Money Supply, Wholesale Price Index (WPI) and Merchandise Exports are the more important determinants of GDP growth and generated the most desirable forecasts (lower forecast errors).

The Effect of Crude Oil Prices on Inflation and Interest Rates in India: Evidence from DCC-GARCH Model

Understanding the empirical linkage between oil prices and inflation is imperative as all monetary authorities attempt to keep inflation under check. This paper examines the time-varying correlations between crude oil prices and two major macroeconomic variables, inflation and interest rates in India. A dynamic conditional correlation GARCH analysis is applied to study the impact of oil price fluctuations on Indian Economy. Results of DCC-GARCH show that correlation between WPI (Wholesale price index) and international crude oil prices remains positive and close to one for majority of period except during the subprime mortgage crisis of 2007-09 when these two become negatively correlated. The results from DCC-GARCH suggests that global crude oil prices have significant effect on inflation but no direct effect on interest rates. However, results from Granger causality test indicates that oil prices will be able to affect interest rates at appropriate lag levels.

The Impact of Macroeconomic Variables on Stock Prices: An Empirical Analysis of Islamabad Stock Exchange

The purpose of this study was to analyze long-run causal relationship between ISE (Islamabad Stock Exchange) and macroeconomic variables in Pakistan and also find out the direction of causality. The impact of macroeconomic variables on stock prices of ISE has not been previously discussed by the researchers. The monthly data from January 2001 to December 2010 was used in this study. The set of macroeconomic variables include Exchange Rate (ER), Foreign Exchange Reserves (FER), Industrial Production Index (IPI), Interest Rate (IR), Imports (M), Money Supply (MS), Wholesale Price Index (WPI) and Exports (X). Descriptive statistics and Unit root test, Johansen Co-integration Technique and Granger Causality Technique were employed to analyze the long-run and causal relationship between the macroeconomic variables and stock prices.  The results revealed that M showed positive and significant relationship but Foreign Exchange Reserves (FER) and Industrial Production Index (IPI) indicated positive and insignificant relationship with the stock prices. Exchange rate(ER), Money supply (MS) and  Whole sale price index(WPI) showed negative but significant relationship while Interest  rate (IR) and Export( X )indicated a negative and insignificant relationship with the stock prices. The findings of Granger Causality revealed that only exports showed a unidirectional causal relationship.Â

Testing Stolper-Samuelson Theorem in the Indian Context

The purpose of this paper is to examine the Stolper-Samuelson Theorem in the context of India which is one of the central results of Heckscher-Ohlin theory. This theorem provides a definite way of analysing the effect of change in the prices of goods on the prices of factors of production due to tariffs. Since the theorem has been couched in terms of increasing tariffs however, the paper attempts to look for obverse of this theorem by emphasising on a certain issue. Since tariffs are declining, then it is argued that import-substituting industries would suffer at the cost of export-promoting industries. The study deals with three variables-Factor Price Ratio (FPR), Terms of Trade (TOT) and Wholesale Price Index (WPI) covering period 1992-2010. Year has been taken as the exogenous variable. The methodology has been developed for the construction of semi-log and multiple regression models to analyse the impact of Terms of Trade on Factor Price Ratio. The paper shows that Stolper-Samuelson Theorem does not hold good in the case of India and it is the Wholesale Price Index which actually shows a favourable impact on FPR.

Inflation in the Indian Economy

Inflation is one of the most retarding factors of economic life and economic development. In fact, it affects almost all economic activities as well as consumption pattern of average and poor people. Since 1947, prices have continuously risen in India. It is seen that fluctuations in prices create an atmosphere of uncertainty which is not conducive to the developmental activities. In other words inflation creates uncertainty in development activities which cause a decline in the purchasing power of money. At the same time, stability in the price level is conducive for economic stability. It is quite interesting to note that what India experiences in instability in the price level are different from Keynesian view who stated that inflation occurs after the achievement of full employment level. But it is not so in India where increase in government expenditure is the major cause to inflation. Hence, the investigators attempt to analyze the inflationary trend and growth of public expenditure in India over a period of time. The fluctuation in price level is measured in terms of wholesale price index or consumer price index.

Comparing the measures of core inflation in India: trimmed mean and structural vector auto-regression approach

This paper estimates core inflation through trimmed mean method and structural vector auto-regression (SVAR) method by using monthly data of wholesale price index (WPI) and index of industrial production (IIP) from April 2005 to March 2014 for India. In this paper, we have compared 25% trimmed mean and SVAR method and it was found that SVAR measure provides better results than trimmed mean method. In SVAR method, we found the exact movements of core and non-core shocks in impulse response functions and variance decomposition. It is based on the definitions of core inflation but trimmed mean method excludes the outliers in the price index, whereas SVAR method is difficult to estimate.

The Relationship between Inflation, Inflation Uncertainty and Output Growth in India

Friedman's hypothesis regarding the relationship between inflation, inflation uncertainty and output growth states that full employment policy objective of the government tends to increase the rate of inflation which increases the uncertainty about the future course of inflation. Increase in inflation uncertainty lowers economic efficiency and reduces output growth. There are very few studies for underdeveloped countries particularly for India regarding the relationship between inflation, inflation uncertainty and output growth. Thornton's (2006) study regarding the relationship between inflation and inflation uncertainty in India is univariate in nature and it cannot establish the relationship between inflation uncertainty and output growth. This study intends use the bivariate GARCH model to find out the relation between inflation, inflation uncertainty and output growth simultaneously. In this study we use monthly data of wholesale price index (WPI) and index of industrial production (IIP) of India as the proxies of price and output respectively from 1950:1 to 2011:12. Following Fountas, Karanasos and Kim (2002) we have used the following bivariate GARCH model to estimate simultaneously the means, variances and covariances of inflation and output growth. We use Granger- causality test to know the statistical relationship between average inflation, output growth, inflation uncertainty and output growth uncertainty. We find strong evidence that increase in average inflation raises inflation uncertainty and increase in growth rate increases the growth rate uncertainty. But we do not find any statistically significant relationship between inflation uncertainty and output growth rate.

The Dimensions of Industrial Growth in Tamil Nadu, India: Three Decades of Experience

Industrial development plays a momentous role in all walks of development. The empirical investigations of world famous works pursued by Simon Kuznets(1966) Chennery(1980), Hoffman(1958), Murray & Bryce(1960) and Kaldor(1978) found that there is a positive and significant association between industrial development and overall development of a nation. In this paper an attempt is made to assess the various dimensions of industrial development of Tamil Nadu, India. To examine the performance of the industrial economy of Tamil Nadu, statistics have been collected from Annual Survey of Industries, published by Central Statistical Organization, Government of India. The variables administered in this work to evaluate the performance of agro based and non agro based manufacturing industries of Tamil Nadu include number of factories, productive capital, employment, value of output and value added. This study covers the period of three decades form 1980-81 to 2010-11, so as to understand the effects of the new economic policy. Further, the entire study period has been classified into two folds as pre reform period (1980-81 to 1990-91) and post reform period as (1991-92 to 2010-11). Collected statistics are deflated using wholesale price index to overcome the price fluctuation. The result obtained using annual compound growth rate reveals that almost all the variables express the same level of growth in both agro and non-agro related industries. But, owing to extraordinary performance of chemical based industries the value added of non- agro related industries reveal a dramatic growth. Mention should be made that the growth of employment has shown a negative sign during the reform period. Hence, it is suggested that the policy makers should frame the effective and suitable policy considering the employment generation. Such kind of strategies will give a new life not only to India but also all the developing countries.

Contributions to a History of Prices in Norway: Monthly Price Indices, 1777-1920

This study reports the outcome of an eort to collect market price data for Norway with a view to constructing monthly price indices from the year 1777 to 1920. The material covers data on commodity prices from agriculture, shery, dairying, manufacturing and mining. Indices of the wholesale and producer price index families are constructed, using the repeat sales method for constructing the underlying price series. Separate indices for commodity exports and imports are also presented. The new wholesale price index, as well as the export and import price indices, are linked to existing price indices after 1920 and brought forward to the end of 1940. The price indices shed new light on two great wartime inationary episodes in Norway: 1807-1817 and 1913-1920. In spite of a 61-fold increase in the price level in the rst period and a 4-fold increase in the second, it is found that, after ination had been brought under control, prices reverted to a level consistent with the purchasing power parity principle.

Macroeconomic Announcements and the Implied Volatility Index: Evidence from India VIX

This study examines the impact of scheduled macroeconomic announcements on the option’s implied volatility index in the emerging market. The macroeconomic indicators considered are RBI monetary policy statements, the consumer price index, wholesale price index, index of industrial production, the employment rate and gross domestic product (GDP growth rate). The study reveals that during non-announcement periods the implied volatility index (India VIX) increases significantly. Once results are announced, uncertainty is resolved and the India VIX returns to normal levels. It confirms that the India VIX declines significantly following scheduled GDP news, but rises significantly on the announcement of monthly inflation rates (WPI). Indeed, the joint effect of the announcements relating to monetary policy, the industrial output, employment rate and GDP is found to be statistically significant (and negative). JEL Classification: E52, E58, G12, G14

Modelling the Relationship between Whole Sale Price and Consumer Price Indices: Cointegration and Causality Analysis for India

The study attempts to analyze the static and dynamic causality between producers’ prices measured by wholesale price index (WPI) and consumers’ prices measured by consumers’ price index (CPI) in case of India. In doing so, we have applied the autoregressive distributed lag (ARDL) bounds testing approach to co-integration and robustness of the ARDL approach which is examined by Johansen and Juselius’ ( 1990 ) maximum likelihood approach over the time period of 1950–2009. We found bidirectional causality between producers’ and consumers’ prices in Indian economy. Variance decomposition (VD) forecast analysis reveals that in India, producers’ prices lead consumers’ prices. This implies that WPI is determined by market forces and also a leading indicator of consumers’ prices and inflation. This gives an indication to the Indian policy analysts to control for factors affecting WPI in order to have control on CPI since CPI is used for indexation purposes for many wage and salary earners including government employees and hence it will be helpful in cutting down the excess government expenditure.

The Gibson paradox: Evidence from China

Recent literature has advanced the view that the Gibson paradox, or the positive correlation of the price level with nominal interest rates, is nearly always a gold standard phenomenon. We argue that the Gibson correlation is more accurately classified as a statistical artifact of commodity money systems, with the gold standard merely representing one such system. Using new evidence from Chinese monetary history, this article gives evidence that the Gibson paradox appeared during China's silver-cored metallic standard era. Estimates obtained from recursive ordinary least squares specifications and vector auto-regressions performed, using the Shanghai Yinchai Rate and the Chinese Wholesale Price Index, confirm a Gibson correlation for China during the period 1873–1924.