scholarly journals Financing housing and house prices in China

2019 ◽  
Vol 12 (4) ◽  
pp. 445-461 ◽  
Author(s):  
Philip Arestis ◽  
Maggie Mo Jia
Keyword(s):  
Time Series Data ◽  
House Prices ◽  
Cointegration Analysis ◽  
Bank Loans ◽  
Series Data ◽  
Shadow Banking ◽  
Content Type ◽  
Positive Effects ◽  
Financing Channels ◽  
The Impact

Purpose This paper aims to examine the evolution of house prices in China and especially the effects of different financing channels on China’s house prices. Design/methodology/approach The author use the own theoretical framework and proceed to test the testable hypotheses by using the autoregressive distributed lag bounds test approach for cointegration analysis and the unrestricted error correction model. Quarterly time series data from Q1 2002 to Q2 2016 are used. Findings The results suggest that in the short run, bank loans to real estate development and scale of shadow banking have significant positive effects on house prices. In the long run, the scale of shadow banking and disposable income affects house prices positively and significantly. Originality/value This study provides more insights into how and to the extent different financing channels affect China’s house prices, particularly the impact of shadow banking on the house prices.

Determinants of Islamic banking growth: an empirical analysis

2018 ◽  
Vol 11 (1) ◽  
pp. 18-39 ◽  
Author(s):  
Tamsir Cham
Keyword(s):  
World Bank ◽  
Time Series Data ◽  
Empirical Work ◽  
Series Data ◽  
Islamic Banking ◽  
Content Type ◽  
Positive Effects ◽  
World Bank Enterprise Survey ◽  
Enterprise Survey ◽  
The Impact

Purpose This paper aims to examine the determinants of growth rate in Islamic banking using annual time series data. Design/methodology/approach The author applied several econometrics methods including generalized linear model and survey-based indicators. The author uses the World Bank Enterprise Survey data to supplement the answers. Findings The results support the view that high oil prices, stable domestic prices, higher educated populace and greater presence of capital resources have positive effects on growth in Islamic banking. The findings, however, revealed that instability adversely affects Islamic banking growth. The author found no clear conclusion on the impact of economic growth, greater presence of Muslim population and presence of sharia in the legal system of the country on growth in Islamic banking. The major constraints impeding Islamic banking growth include regulations, tax rates and skilled labor force. Originality/value There is no empirical work that has been done on the determinants of Islamic banking growth by taking into account the following factors: oil price dynamics, sharia compliant, macroeconomic variables, instability and World Bank Enterprise survey. This paper attempts to search for the push and pull factors of Islamic banking growth to fill the gap in determining the Islamic banking growth.

Impact of monetary policy on house prices: case of Pakistan

2019 ◽  
Vol 13 (3) ◽  
pp. 503-512
Author(s):  
Muhammad Umar ◽  
Moin Akhtar ◽  
Muhammad Shafiq ◽  
Zia-Ur-Rehman Rao
Keyword(s):  
Monetary Policy ◽  
Stock Market ◽  
Time Series Data ◽  
House Prices ◽  
Series Data ◽  
Stock Market Index ◽  
Content Type ◽  
Market Index ◽  
The Impact ◽  
The Relationship

Purpose This study aims to explore the impact of monetary policy on house prices in Pakistan. Design/methodology/approach This study uses monthly time-series data of house prices, monetary policy, inflation and stock market index ranging from January 2011 to December 2016. All the series were checked for stationarity by using augmented Dickey–Fuller test, and lag length of 11 was decided on the basis of Schwert’z rule of thumb. Vector autoregressive (VAR) model was used because the series were not co-integrated. Findings The analysis revealed that monetary policy significantly affects house prices in Pakistan. Tight monetary policy results in lower house prices and vice versa. The relationship between monetary policy and house prices is unidirectional. The study also finds that higher inflation also leads to soaring house prices, but the variation in stock market index does not affect house prices. Originality/value To the best of authors’ knowledge, none of the existing studies explores the impact of monetary policy on house prices in Pakistan. The findings help investors and policy makers to understand the relationship between monetary policy and house prices to make better decisions.

The impact of Benin’s first public procurement code and its amendment on healthcare equipment acquisition prices

2018 ◽  
Vol 18 (4) ◽  
pp. 306-322 ◽  
Author(s):  
Pamphile Thierry Houngbo ◽  
Maikel Kishna ◽  
Marjolein Zweekhorst ◽  
Daton Medenou ◽  
Joske G.F. Bunder-Aelen
Keyword(s):  
Health Care ◽  
Time Series Data ◽  
Good Governance ◽  
Public Procurement ◽  
Linear Regression Analysis ◽  
Interrupted Time Series ◽  
Series Data ◽  
Content Type ◽  
The Impact ◽  
Health Care Equipment

PurposeTo satisfy donors and reduce public procurement acquisition prices, Benin has implemented and amended its first public procurement code guided by top-down principles of good governance.Design/methodology/approachThis study aims to measure the impact of the code and its amendment on public procurement acquisition prices of health-care equipment from 1995 to 2010.FindingsA segmented linear regression analysis was performed using interrupted time-series data. The analysis shows that the code and its amendment did not reduce acquisition prices, indicating the limited impact of the code. The authors recommend the implementation of bottom-up processes in establishing the public procurement system, and the development of a reference pricelist of the most widely used health-care equipment, as possible solutions for improving the effectiveness of the code.

scholarly journals UNEMPLOYMENT AND MONETARY POLICY DYNAMICS IN PAKISTAN: EVIDENCE FROM COINTEGRATION ANALYSIS

2021 ◽  
Vol 9 (1) ◽  
pp. 01-09
Author(s):  
Hina Ali ◽  
Muhammad Zeeshan Ali ◽  
Farhana Nosheen ◽  
Afifa Sadar Ud Din
Keyword(s):  
Monetary Policy ◽  
Price Index ◽  
Time Series Data ◽  
Consumer Price Index ◽  
Development Rate ◽  
Cointegration Analysis ◽  
Series Data ◽  
Policy Dynamics ◽  
Independent Variable ◽  
The Impact

This study examined the impact of monetary policy on unemployment in Pakistan. The time-series data for 1977 to 2019 was taken and the ARDL technique is used for estimation. Unemployment was used as a dependent variable along with other control variables while the money supply was the core independent variable of the research. It was concluded that money related arrangement not just contributes to observing past patterns and additionally future projections of superficial factors of real factors also. The outcomes show that there is a critical and negative connection between spending Deficit and unemployment. The gross domestic product development rate is decidedly identified with unemployment. Populace development rate is adversely identified with unemployment. The consumer price index is contrarily identified with unemployment.

scholarly journals The durability of economic indicators in container shipping demand: a case study of East Asia–US container transport

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tomoya Kawasaki ◽  
Takuma Matsuda ◽  
Yui-yip Lau ◽  
Xiaowen Fu
Keyword(s):  
Time Series ◽  
East Asia ◽  
Time Series Data ◽  
Economic Indicators ◽  
Series Data ◽  
Container Shipping ◽  
Content Type ◽  
The Usa ◽  
Container Movement ◽  
The Impact

Purpose In the maritime industry, it is vital to have a reliable forecast of container shipping demand. Although indicators of economic conditions have been used in modeling container shipping demand on major routes such as those from East Asia to the USA, the duration of such indicators’ effects on container movement demand have not been systematically examined. To bridge this gap in research, this study aims to identify the important US economic indicators that significantly affect the volume of container movements and empirically reveal the duration of such impacts. Design/methodology/approach The durability of economic indicators on container movements is identified by a vector autoregression (VAR) model using monthly-based time-series data. In the VAR model, this paper can analyze the effect of economic indicators at t-k on container movement at time t. In the model, this paper considers nine US economic indicators as explanatory variables that are likely to affect container movements. Time-series data are used for 228 months from January 2001 to December 2019. Findings In the mainland China route, “building permission” receives high impact and has a duration of 14 months, reflecting the fact that China exports a high volume of housing-related goods to the USA. Regarding the South Korea and Japan routes, where high volumes of machinery goods are exported to the USA, the “index of industrial production” receives a high impact with 11 and 13 months’ duration, respectively. On the Taiwan route, as several types of goods are transported with significant shares, “building permits” and “index of industrial production” have important effects. Originality/value Freight demand forecasting for bulk cargo is a popular research field because of the public availability of several time-series data. However, no study to date has measured the impact and durability of economic indicators on container movement. To bridge the gap in the literature in terms of the impact of economic indicators and their durability, this paper developed a time-series model of the container movement from East Asia to the USA.

scholarly journals Fiscal Consolidation and Macroeconomic Variables in India: A Cointegration Analysis

2018 ◽  
Vol 4 (02) ◽  
Author(s):  
Chittaranjan Nayak ◽  
Manaswini Panda
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Empirical Support ◽  
Private Investment ◽  
Cointegration Analysis ◽  
Series Data ◽  
Crowding Out ◽  
Fiscal Deficit ◽  
Fiscal Consolidation ◽  
The Impact

Fiscal consolidation is in the forefront of policy discussion in India since 1990s. But the debate on fiscal consolidation and its real effects has been unable to attain any culmination so far on analytical as well as empirical grounds. The present paper tries to examine the impact of fiscal consolidation on growth, inflation, private investment, and exchange rate in India by analysing a time series data for the period from 1980-81 to 2013-14. The paper observes that there exists a long run relationship between GDP, fiscal consolidation, inflation and private investment. Fiscal deficit reduces GDP significantly. This finding gives empirical support to the neoclassical school of thought. However, the paper does not find any significant crowding-out evidence in India. The conclusion as such is sensitive to lag selection, and inclusion of variables. Although necessary diagnostic checking has been done, a robust analysis warrants a longer time series. The question remains inconclusive that if fiscal deficit does not cause significant crowding-out of private investment, then what are the channels of its negative influence on GDP.

Financial development and economic growth in Tanzania: an ARDL and bound testing approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Saganga Mussa Kapaya
Keyword(s):  
Economic Growth ◽  
Financial Development ◽  
Time Series Data ◽  
Developing Economies ◽  
Financial System ◽  
Principal Component ◽  
Series Data ◽  
Content Type ◽  
Testing Procedures ◽  
Positive Effects

Purpose The purpose of this study is to empirically weigh the evidence for financial depth, liquidity and efficiency role to economic growth, and test for the existence of cointegration between financial development variables and economic growth in Tanzania. Design/methodology/approach The study used the autoregressive distributed lag model with bound testing procedures. The sample covered yearly time-series data from 1980 to 2017, i.e. 38 years. Findings The results suggest that financial system depth is positively related to economic growth in the short run and that financial system liquidity and efficiency is strongly negatively associated with economic growth both in the short and long run. Further, it is found that financial development is cointegrated with economic growth. Thus, financial reforms and liberalisation have not fully brought the desired positive effects on economic growth yet. Originality/value The study uses principal component analysis to capture specific dimensions within the financial system as an intuitive way to aggregate financial development effects. Unlike studies that included several countries with heterogeneous characteristics, which are sometimes difficulty to homogenise, in recognition of countries’ unique experiences, this study uses data from Tanzania as a specific case. It documents pertinent pieces of evidence for a developing economy necessary for financial policy adjustments post the financial and economic liberalisation and reforms period. It nevertheless sheds light on financial policies for other comparable developing economies during and after both financial and economic liberalisation settings.

The impact of embedded location options on price discovery of agricultural futures contracts – the evidence from the Chana contract

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sanjay Mansabdar ◽  
Hussain C. Yaganti ◽  
Sankarshan Basu
Keyword(s):  
Price Discovery ◽  
Time Series Data ◽  
Futures Contracts ◽  
Series Data ◽  
Futures Prices ◽  
Content Type ◽  
Futures Contract ◽  
Agricultural Futures ◽  
Embedded Options ◽  
The Impact

Purpose Embedded options can create asymmetries in information impounded by cash and futures markets, causing errors in price discovery estimation. This paper aims to investigate the impact of embedded location options on measures of price discovery. Design/methodology/approach Various price discovery metrics are computed using observed futures prices that contain embedded location options and cash prices for Chana. Prices of a futures contract that contains no options using observed futures prices and estimates of location option value are synthesized. The price discovery measures are recomputed using synthetic option-adjusted futures contract prices and cash prices, and changes in these measures are attributed to the impact of the embedded location option. Findings If the presence of the location option is ignored, futures appear to dominate price discovery. Once the location option is adjusted for, cash markets are found to dominate price discovery. Research limitations/implications The lack of complete time-series data from the exchange for multiple commodities allows only limited empirical evidence for generalizing conclusions. Practical implications This paper highlights that regulators, exchanges and policymakers in India need to revisit delivery specifications of agricultural commodity futures contracts to enhance their utility from a price discovery perspective. Originality/value This work shows that ignoring the presence of embedded options can cause significant errors in price discovery assessment of agricultural futures contracts, particularly in heterogenous cash markets.

scholarly journals Negative equity in Ireland: estimates using loan-level data

2014 ◽  
Vol 7 (3) ◽  
pp. 327-344 ◽  
Author(s):  
David Duffy ◽  
Niall O’Hanlon
Keyword(s):  
Design Methodology ◽  
Time Series Data ◽  
House Prices ◽  
Age Groups ◽  
Series Data ◽  
Data Set ◽  
Content Type ◽  
Equity Analysis ◽  
Level Data ◽  
Younger Age

Purpose – This paper aims to, using a unique loan-level data set, show the extent to which negative equity in Ireland is concentrated in younger age groups. The sharp decline in house prices since 2007 has led to the emergence of widespread negative equity in Ireland. However, little is known about the type of borrower experiencing negative equity. Design/methodology/approach – This paper uses a unique data set that, for a large sample of mortgages, provides details on both the characteristics of the borrowers and their mortgages. Using this data set, the paper estimates the incidence of negative equity by analysing loans taken out to purchase a primary residence in the period 2005-2012. Findings – The analysis finds the situation in Ireland to be much more severe than that being experienced in other housing market downturns at present, with 64 per cent of borrowers in the period 2005-2012 experiencing negative equity. Analysis by age gives rise to concern, with the majority of those in negative equity aged under 40 years. The paper also points to the large wealth loss experienced by Irish households, in the order of 43 billion, as a result of the fall in property values. Originality/value – The paper is one of the first using loan-level time-series data in Ireland. It highlights the growth in negative equity during the crisis and the extent to which it is concentrated in the younger age groups. It also provides an estimate of the loss in wealth suffered by all households due to the fall in Irish house prices.

Forecasting construction output: a comparison of artificial neural network and Box-Jenkins model

2016 ◽  
Vol 23 (3) ◽  
pp. 302-322 ◽  
Author(s):  
Ka Chi Lam ◽  
Olalekan Shamsideen Oshodi
Keyword(s):  
Neural Network ◽  
Construction Industry ◽  
Time Series Data ◽  
Predictive Accuracy ◽  
Moving Average ◽  
Arima Model ◽  
Series Data ◽  
Effective Response ◽  
Content Type ◽  
The Impact

Purpose – Fluctuations in construction output has an adverse effect on the construction industry and the economy due to its strong linkage. Developing reliable and accurate predictive models is vital to implementing effective response strategies to mitigate the impact of such fluctuations. The purpose of this paper is to compare the accuracy of two univariate forecast models, i.e. Box-Jenkins (autoregressive integrated moving average (ARIMA)) and Neural Network Autoregressive (NNAR). Design/methodology/approach – Four quarterly time-series data on the construction output of Hong Kong were collected (1983Q1-2014Q4). The collected data were divided into two parts. The first part was fitted to the model, while the other was used to evaluate the predictive accuracy of the developed models. Findings – The NNAR model can provide reliable and accurate forecast of total, private and “others” construction output for the medium term. In addition, the NNAR model outperforms the ARIMA model, in terms of accuracy. Research limitations/implications – The applicability of the NNAR model to the construction industry of other countries could be further explored. The main limitation of artificial intelligence models is the lack of explanatory capability. Practical implications – The NNAR model could be used as a tool for accurately predicting future patterns in construction output. This is vital for the sustained growth of the construction industry and the economy. Originality/value – This is the first study to apply the NNAR model to construction output forecasting research.

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