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Book part
Publication date: 19 December 2012

Tae-Hwy Lee and Weiping Yang

The causal relationship between money and income (output) has been an important topic and has been extensively studied. However, those empirical studies are almost…

Abstract

The causal relationship between money and income (output) has been an important topic and has been extensively studied. However, those empirical studies are almost entirely on Granger-causality in the conditional mean. Compared to conditional mean, conditional quantiles give a broader picture of an economy in various scenarios. In this paper, we explore whether forecasting conditional quantiles of output growth can be improved using money growth information. We compare the check loss values of quantile forecasts of output growth with and without using past information on money growth, and assess the statistical significance of the loss-differentials. Using U.S. monthly series of real personal income or industrial production for income and output, and M1 or M2 for money, we find that out-of-sample quantile forecasting for output growth is significantly improved by accounting for past money growth information, particularly in tails of the output growth conditional distribution. On the other hand, money–income Granger-causality in the conditional mean is quite weak and unstable. These empirical findings in this paper have not been observed in the money–income literature. The new results of this paper have an important implication on monetary policy, because they imply that the effectiveness of monetary policy has been under-estimated by merely testing Granger-causality in conditional mean. Money does Granger-cause income more strongly than it has been known and therefore information on money growth can (and should) be more utilized in implementing monetary policy.

Article
Publication date: 2 November 2018

Tadahiro Nakajima

The purpose of this paper is twofold. First, the paper examines the risk transmission between crude oil and petroleum product prices of Japan’s oil futures market. Second…

Abstract

Purpose

The purpose of this paper is twofold. First, the paper examines the risk transmission between crude oil and petroleum product prices of Japan’s oil futures market. Second, it compares the performance of two tests for Granger causality using realized variance (RV) and the exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model.

Design/methodology/approach

The author measures the daily RV of crude oil, kerosene and gasoline futures listed on the Tokyo Commodity Exchange using high-frequency data, and he examines the Granger causality in variance between these variables using the vector autoregression model. Further, the author estimates the EGARCH model based on daily data and test for Granger causality in variance between commodity futures using Hong’s (2001) approach.

Findings

The results of the RV approach reveal that the hypothesis on the existence of a mutual volatility spillover between crude oil and petroleum product markets is accepted. However, the results of the conventional approach indicate that all the hypotheses on Granger causalities in variance are rejected. The methodology based on intraday high-frequency data exhibits higher power than the conventional approach based on daily data.

Originality/value

This is the first paper to investigate Japan’s oil market using RV. The authors conclude that the approach based on RV is universally adoptable when testing for Granger causality in variance.

Details

Studies in Economics and Finance, vol. 36 no. 2
Type: Research Article
ISSN: 1086-7376

Keywords

Article
Publication date: 17 February 2021

Lu Yang, Nannan Yuan and Shichao Hu

To explore the state of this conditional Granger causality when other cities are not factors, we investigate housing market networks in China's major cities by using a…

226

Abstract

Purpose

To explore the state of this conditional Granger causality when other cities are not factors, we investigate housing market networks in China's major cities by using a combination of conditional Granger causality and network analysis.

Design/methodology/approach

Although housing market networks have been well discussed for different countries, the question of housing market networks in China's major cities based on the conditional causality perspective has yet to be answered.

Findings

We discover that second-tier cities are more influential than first-tier cities. Although the connectivity of the primary housing market is more complex than the diversified connectivity observed in the secondary housing market, both markets are scale-free networks that exhibit high stability. Moreover, we reveal that geographic conditions and economic development jointly determine the housing market's modular hierarchical structure. Our results provide meaningful information for both Chinese policymakers and investors.

Originality/value

By excluding the influence of other cities, our conditional Granger causality identifies the true casual relation between cities' housing markets. Moreover, it is the first paper to consider the primary housing market and secondary housing market separately. Specifically, Chinese prefer new house rather than second-hand house from both speculative and self-housing. Generally speaking, the new house price is lower than the second-hand house price since the new house is off-plan property. Therefore, understanding the difference between primary and secondary housing markets will provide useful information for both policymakers and speculators.

Details

International Journal of Emerging Markets, vol. 17 no. 9
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 2 August 2019

Sima Siami-Namini and Darren Hudson

The purpose of this paper is to investigate both linear and/or nonlinear effects of inflation on income inequality and to test the Kuznets hypothesis using panel data of…

2028

Abstract

Purpose

The purpose of this paper is to investigate both linear and/or nonlinear effects of inflation on income inequality and to test the Kuznets hypothesis using panel data of 24 developed countries (DCs) and 66 developing countries (LDCs) observed over the period of 1990–2014.

Design/methodology/approach

This paper explores the short- and long-run Granger causality relationship between inflation and income inequality using the Toda and Yamamoto (1995) procedure and a Vector Error Correction Model (VECM) approach. The existence of a nonlinear relationship between inflation and income inequality is confirmed implying as inflation rises income inequality decreases. Income inequality then reaches a minimum and then starts rising again. The findings of this paper show the existence of Kuznets “U-shaped” hypothesis between income inequality and real GDP per capita in DCs group, and the existence of Kuznets’ inverted “U-shaped” hypothesis for LDCs group.

Findings

The results indicate that there is no bi-directional Granger causality between inflation and income inequality in the short-run, but, there is bi-directional Granger causality in the long-run for both the DCs and LDCs group. The results help us to assess the effectiveness of monetary policy in reducing income inequality in both the DCs and LDCs group. As a policy implication, monetary policy is often aimed at controlling the annual rate of inflation in the long-run with a short-run focus on reducing output gaps and creating employment. However, managing inflation may have implications for income inequality.

Originality/value

This is original research paper which analyzes the “U-shaped” and inverted “U-shaped” paths of income inequality and real GDP per capita for large sample of two group countries including developed and developing countries, respectively. Also, this paper analyzes the nonlinear relationship between inflation and income inequality in two groups. Furthermore, this paper investigates the short- and long-run relationship between variables. The results are important for policy makers.

Details

Journal of Economic Studies, vol. 46 no. 3
Type: Research Article
ISSN: 0144-3585

Keywords

Article
Publication date: 17 August 2018

Narinder Pal Singh and Sugandha Sharma

The purpose of this paper is to investigate the dynamic relationship among Gold, Crude oil, Indian Rupee-US Dollar and Stock market-Sensex (gold, oil, dollar and stock…

Abstract

Purpose

The purpose of this paper is to investigate the dynamic relationship among Gold, Crude oil, Indian Rupee-US Dollar and Stock market-Sensex (gold, oil, dollar and stock market (GODS)) in the pre-crisis, the crisis and the post-crisis periods in the Indian context.

Design/methodology/approach

The authors use Johansen’s cointegration technique, Vector Error Correction Model (VECM), Vector Auto Regression, VEC Granger Causality/Block Exogeneity Wald Test, and Granger Causality and Toda Yamamoto modified Granger causality to study long-run relationship and causality.

Findings

Johansen’s cointegration test results indicate that there is a long-run equilibrium relationship among the variables in the pre-crisis and the crisis periods but not in post-crisis period. VECM results report that none of four models of the variables show long-run causality in the pre-crisis period. During the crisis period, both crude oil and Sensex models show long-run causality. However, in some cases, results indicate short-run causality. The authors find one-way causality from USD and Sensex to crude oil, and from gold and Sensex to USD. Thus, the authors conclude that the relationship among GODS is dynamic across global financial crisis.

Practical implications

The research findings of this study are vital to the large group of stakeholders and participants of gold, crude oil, US dollar and stock market in emerging economies like India. The results are useful to importers, exporters, government, policy makers, corporate houses, retail investors, portfolio managers, commodity traders, treasury and fund managers, other commercial traders, etc.

Originality/value

This study is one of its kinds as it investigates the relationship among GODS in India in different sub-periods like before, during and after the global financial crisis of 2008. None of the studies compare phase-wise relationship among GODS in the Indian context. The study contributes to the economic theory and the body of knowledge. It highlights the need to revisit the economic theory to explain the interplay mechanism among GODS.

Details

Journal of Advances in Management Research, vol. 15 no. 4
Type: Research Article
ISSN: 0972-7981

Keywords

Article
Publication date: 31 May 2011

Chia‐Hsing Huang and Liang‐Chun Ho

This paper seeks to study the impact of bio‐fuel policies on oil and food futures prices from December 6, 2004 to August 1, 2008.

Abstract

Purpose

This paper seeks to study the impact of bio‐fuel policies on oil and food futures prices from December 6, 2004 to August 1, 2008.

Design/methodology/approach

The daily closing prices of brent crude oil, light sweet crude oil, corn, wheat, soybeans, and rough rice futures from December 6, 2004 to August 1, 2008 are used in this research. The vector error correction model is applied in order to study the impact of bio‐fuel policies on oil and agricultural futures prices.

Findings

Unit root and cointegration tests show that the brent crude oil, light sweet crude oil, wheat, corn, soybeans, and rough rice futures are stationary and have a long‐run equilibrium relationship. Granger causality tests of the four periods shows that the causality relationship between oil futures and food futures changes over time. The first period result shows many Granger causes on several variables at a 5 percent significance level. The second period has more Granger causes at the 5 percent significance level. However, the Granger causality relationships become fewer and fewer in the third and fourth period.

Originality/value

This is the first paper to study the impact of the four major bio‐fuel policies of Brazil, the European Union, and the USA.

Details

Journal of Financial Economic Policy, vol. 3 no. 2
Type: Research Article
ISSN: 1757-6385

Keywords

Article
Publication date: 19 January 2023

Monsurat Ayojimi Salami, Harun Tanrivermis and Yeşim Aliefendioğlu (Tanrivermis)

This study aims to establish the relationship between house acquisitions by foreigners (HAF) and house price index (HPI) in Turkey.

Abstract

Purpose

This study aims to establish the relationship between house acquisitions by foreigners (HAF) and house price index (HPI) in Turkey.

Design/methodology/approach

Due to the nature of this study, the data spans from January 2020 to March 2022. The house price index and the number of foreign house acquisitions across three provinces: Ankara, Izmir and Bursa, and national-level data were obtained from the TurkStat database. Consumer price index (CPI) and Turkish interest rates are control variables. In addition, monthly Turkish interest rates and CPI were obtained from the investing.com and TurkStat database, respectively. Furthermore, this study used autoregressive-distributed lag and Toda Yamamoto Granger causality models to avoid analysis bias. HPI and HAF are the variables used to accomplish the objectives of this study.

Findings

This study established a short-run equilibrium between foreign house acquisitions at the provincial and national levels. The short-run deviations were adjusted faster, ranging from 57.53% to 89.24% for some provinces, while Izmir is struggling to adjust at 6.48%. Both unidirectional and bidirectional Granger causality evidence suggests that the Turkish house price index increases at the national and provincial levels. This finding suggests the need for continuous policy intervention in the Turkish housing market because house prices play a pivotal role in Turkish economic development and daily lives.

Research limitations/implications

This study’s scope and single-country study are its limitations. However, those limitations make the findings appropriate for the country of the study rather than generalising the results.

Practical implications

The study provides empirical evidence that foreign housing acquisition contributes negatively to housing affordability in Turkey and calls for authority intervention. This is because housing is considered shelter, a fundamental need to which citizens are expected to be entitled. Most citizens are low- and medium-income earners who may be unable to afford a house out of their income if it becomes costly. Once the expenditure to secure housing exceeds 30% of their income, it is considered unaffordable.

Originality/value

To the authors' best knowledge, this is the first empirical study that established the influence of foreign house acquisitions on Turkish house price increases and adversely reduced house affordability by Turkish citizens. The study is the first on foreign Turkish housing acquisition that used both theory of ownership and justice motivation theory to explain HAF.

Details

International Journal of Housing Markets and Analysis, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 8 November 2022

Kaushik Dey, Amlendu Kumar Dubey and Seema Sharma

This paper aims to focus on the contribution of segregated renewable energy (RE) sources such as solar, wind, bagasse, biomass, small hydropower (SHP) and waste to heat in…

Abstract

Purpose

This paper aims to focus on the contribution of segregated renewable energy (RE) sources such as solar, wind, bagasse, biomass, small hydropower (SHP) and waste to heat in driving sustainable industrial production in India.

Design/methodology/approach

This study uses non-linear modelling techniques such as quantile regression and the non-linear Granger causality test to explore the interplay between segregated RE generation and industrial production in India.

Findings

The study findings support the role of segregated RE sources generation, especially SHP and bagasse, on industrial production in India. This paper finds unidirectional non-linear Granger causality running from segregated RE sources to industrial production. Bidirectional non-linear Granger causality has been established from biomass, waste-heat to index of industrial production and vice versa, supporting an asymmetric feedback hypothesis.

Research limitations/implications

The study findings will aid the energy policymaker in framing policies for RE sources, especially bagasse-based and SHP generation for the sustainable industrial growth of India.

Originality/value

To the best of the authors’ knowledge, this is one of the first studies to explore the role of segregated RE sources generation to drive sustainable industrial growth in India using non-linear techniques.

Details

International Journal of Energy Sector Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1750-6220

Keywords

Book part
Publication date: 24 October 2019

Deniz Ilalan and Burak Pirgaip

Since the famous tapering talk of Bernanke, US Dollar (USD) made a significant appreciation on emerging market local currencies. When the stock indices are adjusted to…

Abstract

Since the famous tapering talk of Bernanke, US Dollar (USD) made a significant appreciation on emerging market local currencies. When the stock indices are adjusted to USD, a negative relationship is usually the case. USD index is a natural candidate for measurement of these effects. It is seen that some emerging stock indices exhibit negative causality with USD index in Granger sense. Moreover, the authors take into account rolling correlations of USD index and the relevant stock indices and examine them on the investment horizon beginning from tapering talk. The authors deduce that Granger causality test and correlation results are coherent with each other which sheds light to the famous discussion whether causality implies correlation or vice versa.

Book part
Publication date: 30 August 2019

Gary J. Cornwall, Jeffrey A. Mills, Beau A. Sauley and Huibin Weng

This chapter develops a predictive approach to Granger causality (GC) testing that utilizes k…

Abstract

This chapter develops a predictive approach to Granger causality (GC) testing that utilizes k -fold cross-validation and posterior simulation to perform out-of-sample testing. A Monte Carlo study indicates that the cross-validation predictive procedure has improved power in comparison to previously available out-of-sample testing procedures, matching the performance of the in-sample F-test while retaining the credibility of post- sample inference. An empirical application to the Phillips curve is provided evaluating the evidence on GC between inflation and unemployment rates.

Details

Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A
Type: Book
ISBN: 978-1-78973-241-2

Keywords

1 – 10 of over 2000