scholarly journals The Indian Inflation 2006–2016: An Econometric Investigation

2019 ◽  
Vol 20 (1) ◽  
pp. 46-69 ◽  
Author(s):  
Paramita Mukherjee ◽  
Dipankor Coondoo
Keyword(s):  
Coming Out ◽  
Price Index ◽  
Consumer Price Index ◽  
Wholesale Price ◽  
Policy Implications ◽  
Fuel Price ◽  
Relative Prices ◽  
Wholesale Price Index ◽  
The Relationship

Recently several changes have been adopted in the conduct of monetary policy in India, like tracking CPI (Consumer Price Index), targeting inflation and so on. However, certain curious features of inflation may have some implications on the effectiveness of such measures. This article tries to explore the nature of inflation during the last decade. There are certain views about the nature of Indian inflation from the structuralist perspective. This article contributes to the literature by empirically testing those propositions and coming out with some significant policy implications. The article is based on monthly data from January 2006 to March 2016. By employing econometric techniques like cointegration and vector autoregression (VAR), the article tries to explain the movements of different components of WPI (Wholesale Price Index) and CPI inflation, both core and headline inflation and how they are related to macroeconomic policy variables. The empirical analyses focus on finding out the existence of co-movements among the inflation and macroeconomic variables, explaining the role of components like food and fuel price in driving CPI and WPI. The results have some important policy implications. First, the movements of WPI and CPI and their headline and core counterparts are not explained by same set of variables. Second, food inflation is not explained by agricultural output pointing to the insufficient increase in supply in agriculture. Third, the determinants of CPI headline and core inflation are not same. So, both of them should be tracked while formulating policies. The relationship among the components of inflation point to the possibility of some adjustment in demand from one set of goods to another, implying adjustments in terms of relative prices which needs further exploration. JEL: E31, E52, C32

scholarly journals Towards inflation targeting in Egypt: the relationship between exchange rate and inflation

2012 ◽  
Vol 15 (3) ◽  
pp. 325-332 ◽  
Author(s):  
Aliaa Khodeir
Keyword(s):  
Exchange Rate ◽  
Inflation Targeting ◽  
Price Index ◽  
Consumer Price Index ◽  
Wholesale Price ◽  
Strong Relationship ◽  
Causality Test ◽  
Wholesale Price Index ◽  
Exchange Rate Movements ◽  
The Relationship

Since the Egyptian economy has recently moved towards inflation targeting, it became very important to know whether exchange rate movements have serious inflationary implications or not. To investigate this subject, the study aims to analyse the relevance of inflation with the exchange rate by using the Granger-causality test. Two indicators of inflation will be used, the consumer price index (CPI) and wholesale price index (WPI). In general, the results show a strong relationship between the two variables in a way that may give support to the application of ‘flexible inflation targeting regime instead of strict inflation targeting regime’.

scholarly journals ESTIMATION OF LONG-RUN RELATIONSHIP OF INFLATION (CPI & WPI), AND OIL PRICES WITH KSE-100 INDEX: EVIDENCE FROM JOHANSEN MULTIVARIATE COINTEGRATION APPROACH

2017 ◽  
Vol 23 (4) ◽  
pp. 567-588 ◽  
Author(s):  
Rizwan RAHEEM AHMED ◽  
Jolita VVEINHARDT ◽  
Dalia ŠTREIMIKIENĖ ◽  
Saghir Pervaiz GHAURI ◽  
Nawaz AHMAD
Keyword(s):  
Crude Oil ◽  
Price Index ◽  
Consumer Price Index ◽  
Wholesale Price ◽  
Impulse Response Function ◽  
Oil Prices ◽  
Crude Oil Prices ◽  
Long Run ◽  
Wholesale Price Index ◽  
Relationship Of

This research is an attempt to framework the applied strides to evaluate the long run relationship among commonly used inflation proxies induces such as, wholesale price index (WPI) and consumer price index (CPI), and crude oil price (COP) with KSE100 index returns. In this research we used monthly data for the time period from July 1995 to June 2016, and thus, in this way total 252 observations have been considered. Time series have been made stationary by applying ADF and PP tests at first difference. Johansen multivariate conintegration approach was used to test the long-term association amongst the considered macroeconomic variables. The results indicated that CPI and COP significantly affect KSE100 index returns that indicated CPI along with COP have foreseen power to impact KSE100 index. In contrary, the results of WPI and COP do not have long run relationship with KSE100 index in case of Pakistani economy. Results of variance decomposition exhibited that the index of LKSE100 was realistically rarer exogenous in connection to distinctive factors, as around 92.31% of its variation was explained due to its own specific shocks. It is concluded that CPI and COP can impact the KSE100 index returns. It is confirmed by the results of impulse response function that there is a positive and long run relationship between KSE100 returns and consumer price index (proxy of inflation) and international crude oil prices.

scholarly journals Money Supply, Deficit, and Inflation in Pakistan

1995 ◽  
Vol 34 (4III) ◽  
pp. 945-956 ◽  
Author(s):  
Mohammad Aslam Chaudhary ◽  
Naved Ahmad
Keyword(s):  
Money Supply ◽  
Price Index ◽  
Consumer Price Index ◽  
Policy Implications ◽  
Structural Factors ◽  
The Public ◽  
The Relationship ◽  
Distribution Of Income ◽  
Double Digit

Inflation is a burning issue in Pakistan. It is generally felt that for several years Pakistan has had a double-digit inflation. The public sector has used a mix of policies to control inflation, and it is also held responsible for its creation. The consumer price index (CPI) increased over 11 percent in 1981-82, and over 12 percent in 1990-91. Similarly, sensitive price index (SPI) increased over 15 percent in 1981-82, and over 12 percent in 1990-91. The GDP deflator was also double-digit for several years. Inflation not only affects sectoral allocation and distribution of income but also generates poverty. A prescription might not be appropriate until the roots of the disease are carefully investigated, which is the very reason for carrying out this study. Studies by Hossain (1990) several others concluded that inflation is a monetary phenomenon in Pakistan, while Bilquees (1988) showed that structural factors explained the inflationary process in Pakistan. It is widely disagreed whether money supply is exogenous or endogenous. Vogel (1974), criticising the monetarist approach, argued that further research is needed on the determination of money supply. Given this background, this study is intended to identify the variables leading to inflation; the nature of money supply, endogenous or exogenous, is also analysed. Section 2 of the study provides a brief review of the literature. A model is developed to study the relationship among fiscal deficit, money supply, and inflation. Section 3 contains a description of the empirical results. Section 4 provides the conclusion and policy implications.

scholarly journals Statistical Method to predict Agricultural CPI

2020 ◽  
Vol 8 (12s3) ◽  
pp. 59-62
Keyword(s):  
Urban Areas ◽  
Price Index ◽  
Consumer Price Index ◽  
Wholesale Price ◽  
Market Value ◽  
Goods And Services ◽  
Consumer Prices ◽  
Wholesale Price Index ◽  
Future Prediction ◽  
The Cost

The growth of any country depends on its economy and economic growth is nothing but an increase in the inflation i.e. adjusted market value of the goods and services produced by an economy over time. Statisticians conventionally measure such inflation using the price indices. They are mainly WPI (Wholesale Price Index and CPI (Consumer Price Index). WPI is now known to be an older method of computation because the main focus has to be on consumer prices.CPI is a measure of consumer prices over a certain period. Changes in the CPI are used to assess price changes associated with the cost of living. It can be calculated for rural, urban areas as well as for both. In CPI rural, the workers and labourers are benefitted as their daily wages can be predicted by this approach. The CPI by state data represents the inflation of each of the states giving a concise view of the country. The data is collected and analysed using a mathematical approach called linear regression in future prediction for rural labours based on previous data.

scholarly journals Modeling Commodity Prices, Inflation And Monetary Policy Response

2010 ◽  
Vol 9 (11) ◽  
Author(s):  
Punita Rao
Keyword(s):  
Monetary Policy ◽  
Price Index ◽  
Consumer Price Index ◽  
Wholesale Price ◽  
Commodity Prices ◽  
Rate Of Change ◽  
Inflation Forecasting ◽  
Wholesale Price Index ◽  
Personal Consumption ◽  
Index Measurement

Inflation is generally defined as the rate of change of some price index. Well known examples are the Consumer Price Index, Wholesale Price Index and the personal consumption expenditure price Index. Measurement and forecasting of these indices has been a subject of ongoing debate and research in recent years. This paper attempts to contribute to the debate within the limits of an empirical and country specific. Section 1 deals with the transmission of Monetary policy to growth. Section 2 examines a simple model of inflation forecasting. Section 3 addresses the unfinished debate on Prices and Monetary management.

Wholesale and Retail Prices in the Nineteenth Century

1958 ◽  
Vol 18 (3) ◽  
pp. 298-316 ◽  
Author(s):  
Ethel D. Hoover
Keyword(s):  
World War I ◽  
Price Index ◽  
Consumer Price Index ◽  
Wholesale Price ◽  
Department Of Agriculture ◽  
Goods And Services ◽  
Wholesale Price Index ◽  
Price Indexes ◽  
Retail Prices ◽  
Bureau Of Labor Statistics

Today's best-known price indexes for Wholesale Price and Consumer Price Indexesthe Unitedof theStates are the Bureau of Labor Statistics, and the Indexes of Prices Received and Paid by Farmers, issued by the Department of Agriculture. These indexes, however, are comparatively new. The “Wholesale Price Index” dates from 1902 with indexes covering the years 1890-1901. The “Consumer Price Index” is of even more recent origin. Retail food price indexes were established on a regular basis in 1901, again with data back to 1890. Other goods and services were not added until after World War I, with estimates back to 1913 based on special studies in shipbuilding cities. The “Index of Prices Received by Farmers” was issued by the Department of Agriculture in 1924 and “Prices Paid by Farmers” in 1928. Botfi of these series were extended back to 1910.

scholarly journals EXCHANGE RATE PASS — THROUGH TO DOMESTIC PRICES: EVIDENCE FROM PAKISTAN

2019 ◽  
Vol 2 (1) ◽  
pp. 1-14
Author(s):  
FARHAN AHMED SHAIKH ◽  
SYED MUHAMMAD AHSAN HUSSAIN
Keyword(s):  
Exchange Rate ◽  
Impulse Response ◽  
Price Index ◽  
Consumer Price Index ◽  
Wholesale Price ◽  
Variance Decomposition ◽  
Wholesale Price Index ◽  
Domestic Prices ◽  
Pass Through ◽  
Exchange Rate Pass Through

Exchange Rate Pass — Through is the phenomena that explains to what extent the movements in exchange rate affect macroeconomic variables of any economy. This paper analyses the movements of exchange rate that has affected on wholesale price index, consumer price index, large scale manufacturing, fuel and lightening and the growth of money supply. The data from June 2005 to June 2011 is analyzed by using the econometric framework. In this study, the econometric model, recursive VAR, suggested by McCarthy (2000), is applied in order to measure the movements of exchange rate pass — through to domestic prices by using the impulse response function and variance decomposition. In this study, the results of the impulse response have shown that impact of exchange rate pass through is high on wholesale price index. While the results of the impulse response have shown that the impact of exchange rate pass through is much lower for Consumer Price Index. The result of the variance decomposition has shown that the variance decomposition is indicating that for the CPI variance decomposition is as much as the 5.48 percent. For the WPI the variance decomposition is as much as 10.15 percent and the other variations are explained by the other independent variables.

scholarly journals COVID-19 uncertainty and sleep: the roles of perceived stress and intolerance of uncertainty during the early stage of the COVID-19 outbreak

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Dan Wu ◽  
Tingzhong Yang ◽  
Daniel L. Hall ◽  
Guihua Jiao ◽  
Lixin Huang ◽  
...  
Keyword(s):  
Path Analysis ◽  
Perceived Stress ◽  
Mediation Analysis ◽  
Early Stage ◽  
Intolerance Of Uncertainty ◽  
Policy Implications ◽  
Self Report ◽  
Poor Sleep ◽  
The Relationship

Abstract Background The COVID-19 pandemic brings unprecedented uncertainty and stress. This study aimed to characterize general sleep status among Chinese residents during the early stage of the outbreak and to explore the network relationship among COVID-19 uncertainty, intolerance of uncertainty, perceived stress, and sleep status. Methods A cross-sectional correlational survey was conducted online. A total of 2534 Chinese residents were surveyed from 30 provinces, municipalities, autonomous regions of China and regions abroad during the period from February 7 to 14, 2020, the third week of lockdown. Final valid data from 2215 participants were analyzed. Self-report measures assessed uncertainty about COVID-19, intolerance of uncertainty, perceived stress, and general sleep status. Serial mediation analysis using the bootstrapping method and path analysis were applied to test the mediation role of intolerance of uncertainty and perceived stress in the relationship between uncertainty about COVID-19 and sleep status. Results The total score of sleep status was 4.82 (SD = 2.72). Age, place of residence, ethnicity, marital status, infection, and quarantine status were all significantly associated with general sleep status. Approximately half of participants (47.1%) reported going to bed after 12:00 am, 23.0% took 30 min or longer to fall asleep, and 30.3% slept a total of 7 h or less. Higher uncertainty about COVID-19 was significantly positively correlated with higher intolerance of uncertainty (r = 0.506, p < 0.001). The mediation analysis found a mediating role of perceived stress in the relationship between COVID-19 uncertainty and general sleep status (β = 0.015, 95%C.I. = 0.009–0.021). However, IU was not a significant mediator of the relationship between COVID-19 uncertainty and sleep (β = 0.009, 95%C.I. = − 0.002–0.020). Moreover, results from the path analysis further showed uncertainty about COVID-19 had a weak direct effect on poor sleep (β = 0.043, p < 0.05); however, there was a robust indirect effect on poor sleep through intolerance of uncertainty and perceived stress. Conclusions These findings suggest that intolerance of uncertainty and perceived stress are critical factors in the relationship between COVID-19 uncertainty and sleep outcomes. Results are discussed in the context of the COVID-19 pandemic, and practical policy implications are also provided.

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