Wholesale Price Index Research Articles

The macroeconomic effects of increase and decrease in oil prices: evidences of asymmetric effects from India

PurposeThe purpose of this paper is to assess whether oil price shocks emanating from oil price increase and decrease have a different impact on the macroeconomic activity.Design/methodology/approachThis study conducts the empirical analysis using structural vector auto-regressive model on Indian data for the period from 1996 to 2017. This paper uses four key macroeconomic variables, namely, real gross domestic product (GDP), the real rate of interest, real money supply, wholesale price index inflation and various linear and non-linear measures of oil price shock.FindingsEmpirical results confirm that oil price shock has a significant impact on various macroeconomic variables used in the study. Specifically, shocks emanating from a decline in oil price have a stronger positive impact on real GDP, whereas, a shock due to the rise in oil price has a weaker negative impact on real GDP. Impulse responses confirm that shocks due to a decline in oil prices are long-lasting compared to similar shocks due to a rise in oil prices. Therefore, this study concludes that the macroeconomic impact of oil price shock is asymmetric in India.Originality/valueThis paper adds the following new insights: First, this paper presents a distinct relationship between the growth rate of oil price and GDP during increasing and decreasing phases of oil price to drive home the case for this study. Second, India has adopted crucial administrative initiatives such as deregulation of the market for petroleum products and the promotion of renewable energy during the study period. Finally, previous studies have revealed specific behavioral and economic features of people in India with respect to the demand for petroleum products. In light of these factors, this paper based on Indian experience would be justified.

A Bond Price Puzzle: A Partial Hedge Against the Chinese Hyperinflation

This paper studies how bond traders' extreme beliefs of repayments led to bond market anomalies. The conventional valuation model states that the value of a bond is the sum of the present values of its future cash flows. However, the prices of the consolidated government bonds soared up to thousands of times their face values from 1946 to 1948 during the Chinese Civil War. I find that (1) the bond prices anchored the Shanghai wholesale price index amid hyperinflation; (2) the extreme price pattern was primarily explained by the bond traders’ evolving belief that the government would repay the bonds with an appropriate multiplier after implementing the Currency Reform; (3) the belief was significantly affected by relevant news about repayment. On a weekly average basis, one more positive news about the Currency Reform will lead to an 8.8 percentage points increase in bond price growth rate, while one additional negative news about the repayment with multipliers will decelerate the growth rate by 8.2 percentage points; and (4) at least before the eve of the Currency Reform, the Shanghai financial markets were not sensitive to political uncertainties resulting from the Civil War.

Revisit the relationship between two inflation indicators: Case of Pakistan

This research paper determines the association between two inflation indicators, consumer price index and wholesale price index in three groups' i.e. general group, food group, and non-food group. The objective is to f ind out if the relationship is unidirectional or bidirectional between CPI and WPI in all groups. For this purpose monthly data from July 1971 to December 2019 has been used. Furthermore, Cointegration has been calculated via Johansen's cointegration test on time series data to discover if the long-run aff iliation occurs between the variables. Before cointegration, it is essential to discover the stationarity of the variables for which the augmented dickey fuller test has been used at the f irst difference. Vector Error Correction Model (VECM) is also employed to check for the disturbances of divergence or convergence f inally Granger causality/Block exogenity test is applied to discover causality between variables, it also specifies unidirectional relationship or bidirectional relationship. As a result, it is found that there is a signif icant co-integration equation which indicates that there is an existence of long-run association amongst variables. On the other hand, there is also an indication of the short-run relationship among variables. Finally, a two-way causal relationship is indicated by the granger causality test, between CPI and WPI in general and food group and one-way causal association between CPI and WPI in the non-food group.

Exchange Rate Pass Through Viewed from Wholesale Price in Indonesia

This paper explores the effect of changes in exchange rates on domestic prices, known as Exchange Rate pass Through. The data used in this study are data on the economy in Indonesia in the period 1997.3 to 2017.4. The analytical tool used is multiple regression with the Error Correction model approach. Based on the results of the analysis conducted shows that the effect of the exchange rate on the wholesale price index in the long run is greater than the short run. This shows that the effect of the ex-change rate on domestic prices is indirect.The foreign interest rates variabel effect to wholesale price index in the long term, while the domestic interest rates effect in the short and long term. The effect of foreign prices on the wholesale price index is much larger in the short than in the long-term.

Statistical Method to predict Agricultural CPI

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.

Dynamic Nexuses between Macroeconomic Variables and Sectoral Stock Indices: Reflection from Indian Manufacturing Industry

Determination of significant sector specific macroeconomic factors under the board manufacturing industry is an important task. In Indian context, using the monthly data on five major manufacturing sector specific indices (such as BSE-Basic Materials, BSE-Consumer Discretionary Goods and Services, BSE-Fast Moving Consumer Goods, BSE-Health Care and BSE-Industrials) and the macroeconomic variables (gold price, index of industrial production, wholesale price index, money supply, foreign portfolio investment ratio (FPIR), rate of interest, real effective exchange rate and crude oil price and economic policy uncertainty) for the period September, 2005 to November, 2016, the present study attempted to explore the significant sector specific macroeconomic variables in long run as well as short run. The empirical results obtained by applying the ARDL-UECM model suggested that economic policy uncertainty, FPIR and price factor were observed to be the most important determinants of all the five sectoral stock indices for the study period.

Macroeconomic Determinants of Gold Prices : A Bounds Testing Approach

Despite the demise of gold as a long-standing anchor in the international monetary system, it keeps on alluring its producers, consumers, investors, and speculators over the globe. India is the largest consumer and importer of gold in the world. The investment demand for gold is ascending in India since it is considered as a safe haven. Notwithstanding, high instability in gold prices brings up an issue on its supporting properties. Thus, an attempt was made to identify the macroeconomic determinants of gold prices in India. The study was set to examine the long run as well as short run relationship between gold prices and some macroeconomic variables like BSE Sensex, wholesale price index (WPI), and index of industrial production (IIP) as a proxy of gross domestic product, interest rates, Indian rupee - U.S. dollar exchange rate, and gold reserves of the country. Using the monthly data from April 1995 – March 2018, the relationship was explored empirically by using the autoregressive distributed lag model and error correction model. The ARDL results suggested that the long run cointegration between the prices of gold and the macroeconomic variables during the period of the study and gold reserves of RBI, BSE Sensex, WPI, exchange rate, and IIP were found to be significantly affecting the gold prices. However, interest rates were found to be statistically insignificant during the period of the study. The error correction term, which was negative and highly significant, confirmed the convergence to the long run equilibrium. The results of this study have important implications for the Indian economy and will be helpful for policy formulation.

Exchange rate (USD/INR) pass‐through and wholesale price index: A flexible least square approach

AbstractThe paper explores the exchange rate (USD/INR) pass‐through and the wholesale price index in India. Exchange rate pass‐through (ERPT) has a stimulated effect on the wholesale prices over the period of time. We use flexible least square approach to estimate time varying approach of ERPT and wholesale price, monthly data for the period from April 1994 to May 2019, find exchange rate over the period of time as well as change the wholesale price. It implies that the ERPT provides heterogeneity information that change the whole price index, even both export/import goods and services play a vital role in fluctuating on exchange rate and also change whole price in the domestic market.

Do macroeconomic factors impact corporate debt? Evidence from India

We study the impact of macroeconomic factors on corporate debt in India during April 2000 to March 2018 period using quantile regression. Our quantile regression outcomes reveal that the impact of consumer price index on corporate debt is significant and positive across the quantiles. However, the wholesale price index has a significant and negative impact on debt level. Interest rate and exchange rate do not show similar impact across the quantiles. In this paper, the results of quantile regression are also compared with ordinary least squares regression. The results of ordinary least squares regression indicate that all macroeconomic factors under study affect the corporate debt level.

Consumer price index prediction using Long Short Term Memory (LSTM) based cloud computing

Long Short Term Memory (LSTM) is known as optimized Recurrent Neural Network (RNN) architectures that overcome the lack of RNN’s about maintaining long period of memories information. As part of machine learning networks, LSTM also notable as the right choice for time-series prediction. Inflation rate has been used for decision making for central banks also private sector. In Indonesia, CPI (Consumer Price Index) is one of best practice inflation indicators besides Wholesale Price Index and The Gross Domestic Product (GDP). Since CPI data could be used as a direction for next inflation move, we conducted CPI prediction model using Long Short Term Memory Method. The network model input consists of 34 variables of staple price in Surabaya and the output is CPI value. In the interest of predictive accuracy improvement, we used several optimization algorithm i.e. Stochastic Gradient Descent (sgd), Root Mean Square Propagation (RMSProp), Adaptive Gradient (AdaGrad), Adaptive moment (Adam), Adadelta, Nesterov Adam (Nadam) and Adamax. The result indicate that Nesterov Adam has 4.088 RMSE’s value, less than other algorithm which indicate the most accurate optimization algorithm to predict CPI value.

How would indian economy become worth $ 5 trillion? Performance of selected variables for previous few years conveys a different state of affairs

Now a days, it has been frequently listened that Indian Economy would become worth $5 trillion by the end of 2024. The present government seems to be all committed to reach this mammoth target only in dialogues and speeches. Success or failure of any economy depends upon the efficiency and effectiveness of the government because the government plans, formulates policies or strategies, implements the same and deploys resources. No doubts, the external environment such as conditions prevalent in the global economy also put impact on the individual economies yet the government has a crucial role to play therein. Through this article, the authors have tried to evaluate the Indian economy on the basis of the performance of selected seven variables (GDP growth rate, Fiscal Deficit as % of GDP, Inflation Rate (Retail Consumer Price Index and wholesale Price index), Volume of Foreign Exchange Reserves, Output Growth Rate of Primary, Secondary and Tertiary Sectors, International Hunger Index) for the period of three years starting from 2016-17 to 2018-19. This article is based on the secondary data accessed from various websites and articles available online through internet. The performance of Indian economy is worth appreciating as far as Fiscal Deficit, Inflation and Foreign Exchange reserves are concerned, but the position for the rest of the variables has not been satisfactory. So the target of becoming $ 5 trillion economy seems too difficult to be achieved, if not impossible.

An Alternative Version of Purchasing Power Parity

AbstractA vast literature on Purchasing Power Parity (PPP) has evolved and PPP has become the most popular concept in international finance. PPP is applied with various price indices such as consumer price index, wholesale price index, etc. In this article, we introduce a revised version of PPP equation for financial products, which is strongly supported by our panel data analysis.

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

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.

Prediksi Indeks Harga Konsumen Menggunakan Metode Long Short Term Memory (LSTM) Berbasis Cloud Computing

Long Short Term Memory (LSTM) is known as optimized Recurrent Neural Network (RNN) architectures that overcome RNN’s lact about maintaining long period of memories. As part of machine learning networks, LSTM also notable as the right choice for time-series prediction. Currently, machine learning is a burning issue in economic world, abundant studies such predicting macroeconomic and microeconomics indicators are emerge. Inflation rate has been used for decision making for central banks also private sector. In Indonesia, CPI (Consumer Price Index) is one of best practice inflation indicators besides Wholesale Price Index and The Gross Domestic Product (GDP). Since CPI data could be used as a direction for next inflation move, we conducted CPI prediction model using LSTM method. The network model input consists of 28 variables of staple price in Surabaya and the output is CPI value, also the entire development of prediction model are done in Amazon Web Service (AWS) Cloud. In the interest of accuracy improvement, we used several optimization algorithm i.e. Stochastic Gradient Descent (sgd), Root Mean Square Propagation (RMSProp), Adaptive Gradient(AdaGrad), Adaptive moment (Adam), Adadelta, Nesterov Adam (Nadam) and Adamax. The results indicate that Nadam has 4,008 RMSE’s value, less than other algorithm which indicate the most accurate optimization algorithm to predict CPI value.

The Relationship Between Inflation and Gold Price: Evidence From Sri Lanka

Gold is most sacred metal among Sri Lankans due to it security and high demand. Gold is treated as an alternative investment avenue. It is often stated that gold is the best preserving purchasing power in the long run. Gold investment can also be used as a hedge against inflation and currency depreciation. Therefore, investors are showing interest in investing in the gold due to economic vulnerability. From an economic and financial point of view, movements in the price of gold are both interesting and important. It cannot be denied that gold price is stable all the time and has minimal fluctuation for economic volatility and financial condition. The price of gold is affected by various factors like inflation, crude oil, exchange rate etc. But gold prices are fluctuated by inflation significantly. Gold prices control the inflation instability. Therefore, deep understanding of the relationship between inflation and gold price is prerequisite. The ultimate objective of the study is to explore the relationship between inflation and gold price. The dependent variable is gold price which is measured by Sri Lanka rupee per Troy ounce meanwhile the independent variable is inflation which is measured by wholesale price index. 240 monthly observations from January 1999 to December 2018 were used in the study. Unit root test, correlation analysis, ordinary least square regression analysis, granger causality test and normality tests are employed for analysing data. The empirical results have found strong and positive correlation between inflation and gold price. The results of regression analysis revealed that inflation significantly impacts on gold price. Unidirectional relationship was found between gold price and inflation.

An analysis of Indonesia’s shrinking food security policy space under the WTO

Achieving food security remains a challenge for many low- and middle-income countries, including Indonesia. The aim of this study was to assess the policy space to implement food security policy in Indonesia under the World Trade Organization (WTO). The policy space for developing countries to implement administered prices for agricultural commodities is significantly circumscribed by the Agreement on Agriculture (AoA) under the WTO regime. In particular, the procurement of foodgrains at administered prices is considered “trade distorting support” and limited under the amber box. This study describes the food security policy context in Indonesia, compares existing food procurement expenditure to Indonesia’s commitments within the AoA, and evaluates the implications of different options proposed regarding public stockholding for food security purposes at the WTO. Administered prices and public procurement form part of Indonesia’s long-term commitment to food security policy, and aim to stabilize food prices for producers and consumers. Indonesia’s procurement of rice has been rising as a percentage of value of production (VoP). It is still under the de minimis limit (10%), but the applicable permissible limit on procurement has declined by nearly half, in terms of volume. This indicates that the policy space for providing product specific support is declining, as inflation is not accounted for under the AoA method of calculation. Of the different options that have been tabled to take into account inflation, using the Wholesale Price Index as a deflator increases the policy space the most. The peace clause deliberations at the WTO are of critical importance to the Government of Indonesia, as their policy space becomes increasingly constrained. In the near future, Indonesia may need to invoke the peace clause to restrain other countries from challenging its food security program.

Inflation Dynamics and Monetary Policy in India: A New Keynesian Phillips Curve Perspective

The present study estimates various specifications of the New Keynesian Phillips Curve (NKPC) models for India over 1996Q2 to 2017Q2 using Consumer Price Index (CPI) and Wholesale Price Index (WPI) inflation, separately. The empirical results suggest that the data support all the specifications of the Phillips curve models based on both the CPI and WPI inflations. However, the backward looking and hybrid models provide robust results for both the inflation indices. While the forward-looking behaviour dominates the CPI inflation trajectory, the backward-looking behaviour greatly influences the trajectory of WPI inflation. Also, a small-to-moderate degree of persistence is evident in both the CPI and WPI inflation. The output gap, which mainly represents the demand side pressures, turns up the major force determining both the CPI and WPI inflations. Besides the output gap, real effective exchange rate (reer), international crude oil price inflation, global non-fuel commodity price inflation and rainfall have a modest impact on the CPI and WPI inflations.JEL Classification: E12, E52, C36, C14

An Economic Analysis on Historic Inflation Rate in India

India's inflationary experience was a varied basket. There were some years the annual inflation rate reached a maximum of 40%, while other years were negative. Wholesale price index, differs in a wide range as the lowest value of -12.5% for the year 1952-53 and the highest amount of 38.3% for the year 1943-44. The highest value is due to the end of the world war-II. The years of high, inflation is mainly the impact of War, low agricultural production due to drought and oil price hike up in foreign countries. The inflation rate was below 6% for 38 years and above 6% for 40 years out of 78 years beginning from 1939-40 to 2016-2017. Suppose, it is assumed that India's bearable rate of Inflation is equal to or below 6%, then, India appears to be worst in controlling inflation.
 On the other hand, the rate of inflation above 6% to 15% was for 31years and above 15% for nine years. Therefore, many accept as accurate that India is to be an Inflation driven country. The severe economic setback in the Indian economy is inflation, which hinders the economic power of the people. Most of the people are still suffering due to increase in India. These major study aims to support the Government, and economists should generate better policies for the control the rise.

Impact of Macro Economic Indicators affecting Indian Stock Markets: Evidence from Pre- and Post-Crisis

Volatility is quite evident in stock market fluctuations and often economic factors results in share prices movements. However, there are some fundamental elements, which have a strong impact over the fluctuations of the stock market by and large. This study empirically tested the interconnection between macro-economic factors and Indian stock market. By applying multivariate regression analysis, the effect of macro-economic factors on Indian stock market is tested. The explanatory variables are Wholesale Price Index (WPI), Index of Industrial Production (IIP), Money Supply (M3), Consumer Price Index (CPI), Exchange Rate (ER), Call Money Rate (CMR), Gold Price (GP), Foreign Institutional Investment (FII) and Trade Balance (TB) while explained factors are average monthly closing prices of BSE Sensex and S&P Nifty. Further, for testing the interconnection between macro-economic factors and Indian stock market Pearson's correlation, Factor Analysis and Multiple Regression test have been applied. Three variables namely Economy Rates, Macro Environment and Foreign Investment are obtained by using Principal Component Technique (varimax pivot). It shows that all elements play critical role in affecting the stock market.

Impact of Commodity Futures on Inflation: Perception and Reality

Though it has been proved in many studies that commodity futures trading has a negligible effect on inflation, the relationship between commodity futures trading and inflation cannot be denied completely. In order to curb inflation, the Government of India banned futures trading on wheat, rice, tur, and urad in January 2007 and on chickpea, potato, rubber, and soybean on May 7, 2008. We, in the current study, examined the impact of commodity futures trading on inflation by considering seven agricultural commodities. The current study considered the wholesale price index of the above-mentioned commodities during the 5 year period from 2007 to 2011. Though there were evidences wherein the futures trading influenced the spot prices thereby causing inflation, the ban on futures trading is not the solution to curb inflation. The realistic approach to curb inflation lies in identifying all the factors causing for price rise instead of banning futures trading on selected commodities and waiting for a positive outcome.