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The purpose of this study is to determine whether house prices and income share a stable, stationary relationship in the G-7 countries. This stable relationship has been clearly implied by theory but has been difficult to uncover empirically in previous studies.

The analysis entails using nonlinear tests for a stationary relationship between home prices and per-capita income for the G-7 countries, whereas most previous papers on the topic have used linear methods.

When the standard linear ADF test is used, no stationary relationship for home prices and income is found for any of the G-7 countries. When the more powerful (but still linear) Ng–Perron test is used, the USA, but no other G-7 country, exhibits a stable relationship between the two variables. When the nonlinear Enders–Granger test is used, stationarity between home prices and income is found for five of the remaining six G-7 states.

Previous research has shown that as house prices have risen far above the income, especially over bubble periods, income has done a poor job in predicting home values. The findings show that income has a clear long-run stationary relationship with home values. This implies income could be helpful in providing home price forecasts.

Where previous studies have failed to find a long-run relationship between home prices and income while using linear methods, results in this paper show this theoretical asset–pricing relationship holds once the adjustment process is allowed to exhibit nonlinearity.

The purpose of this study is to measure the effect of land degradation and the environmental changes on agricultural productivity in Somalia, as well as the other factors that affect crop production in Somalia.

Cobb-Douglas production function assumes crop production as a dependent variable and land degradation, labor, capital, fertilizer and climate change as the explanatory variables. In this study time-series data (1962–2017) collected from the Food and Agriculture Organization and World Development Indicators were used. The unit root of the data was examined using Ng-Perron and the Lee-Strazicich methods to explore the unit root property of the breaks. Structural breaks are observed using the Chow test, and the long-run relationship between the variables is examined using Gregory and Hanssen's approach.

This study found that land degradation and climate change have a negative relationship with agriculture production in Somalia. Land degradation leads to the decline in agricultural production as the loss of one hectare of land due the depletion causes agriculture production of Somalia to fall by about five percent. Climate changes and warming of the environment lead to the reduction of agriculture production. One degree Celsius rise in the temperature leads to a three percent decline in agricultural production. Capital contributes immensely to agricultural production as one unit of additional capital raises production by seven percent. The contribution of labor to agricultural production is limited because of land contraction

Land degradation is a significant contributor to the decline of agricultural production. As land degradation continues to worsen, rural poverty increases, which in turn causes the rural migration and the social conflict. The government should develop land improvement programs such as increasing market orientation of the farmers, encourage private sector engagement in agribusiness and establish a regulatory framework of the land uses.

This study examines the structure of the time-series and specifies the break periods to determine when and where significant and sudden changes occurred within land degradation and agricultural production. The study employs advanced econometric methods, namely, Ng-Perron method and the Lee-Strazicich method to test the unit root property of the breaks. It also examines the long-run relationship between the variables using Gregory and Hanssen's approach.

The purpose of this paper is to examine the validity of the purchasing power parity (PPP) hypothesis for two Southern African countries, namely: Lesotho and Zambia.

The authors utilized four econometric tests to examine the existence of the PPP hypothesis in Lesotho and Zambia. These tests include two unit root tests without structural breaks – the Dickey-Fuller generalized least squares (DF-GLS) test and the Ng-Perron test; and two unit root tests with structural breaks – the Perron test and the Zivot-Andrews test. The authors’ empirical analysis is based on an annual data set with varying time periods. The sample period spanned 1960-2010 and 1955-2010, for Lesotho and Zambia, respectively.

The authors found that the PPP hypothesis was supported in the case of Lesotho, but rejected in the case of Zambia.

This paper is the first to simultaneously explore the exchange rate policies, trends, and the PPP for these two countries. The implication of this finding is that Lesotho is unlikely to profit immensely from trade and investment arbitrages; whereas Zambia is more likely to profit immensely from trade and investment arbitrage by trading with the USA. Moreover, the authors’ findings indicate that the PPP doctrine may be a useful guide for the exchange rate and other macroeconomic adjustment policies in Lesotho but not in Zambia.

The purpose of this paper is to examine the relationship between financial development and income inequality in India using annual data from 1982-2012.

Stationarity properties of the series are checked by using ADF, DF-GLS, KPSS and Ng- Perron unit root tests. The paper applied the auto regressive distributed lag (ARDL) bound testing approach to co-integration to examine the existence of long run relationship; and error correction mechanism for the short run dynamics.

The co-integration test confirms a long run relationship between financial development and income inequality for India. The ARDL test results suggest that financial development, economic growth, inflation aggravates the income inequality in both long run and short run. However, trade openness reduces the gap between rich and poor in India.

The present recommend for appropriate economic and financial reforms focussing on financial inclusion to reduce income inequality in India.

Till date, there is hardly any study that makes a clear comparison between market-based indicator and bank based indicator of financial development in India and those examining the relationship between finance and income inequality nexus. Further there is hardly any study to include gini coefficient as a proxy for inequality for India and apply ARDL techniques of co-integration, using the basic principles of GJ hypothesis and provide short run and long run dynamics for India. So the contribution of the paper is to fill these research gaps.

The purpose of this paper is to investigate the impact of financial development on the rural‐urban income inequality in India using annual data from 1965 to 2008.

The Ng‐Perron unit root test is utilised to check for the order of integration of the variables. The long run relation is examined by implementing the ARDL bounds testing approach to cointegration.

The results confirm a relation among the variables. Evidence suggest that financial development, economic growth and consumer prices aggravate rural‐urban income inequality in the long run.

The present study offers fresh insights to policy makers on crafting appropriate policies that reduce rural‐urban income inequality in India.

The contribution of this paper is lies in extending the literature in the context of India towards an extensively researched area of rural‐urban divide but in time series framework and utilization of a better approach of time series approach, i.e. ARDL. Specifically, to the best of the authors' knowledge, this is the first empirical study to test poverty‐finance nexus using the basic principles of the GJ hypothesis and provide evidence of short‐ and long‐run dynamics on the postulated relation for India.

The purpose of this paper is to examine the relationship between financial sector development and poverty reduction in India using annual data from 1970 to 2012. The paper attempts to answer the critical question: does financial sector development lead to poverty reduction?

Stationarity properties of the series are checked by using Ng-Perron unit root test. The paper uses the Auto Regressive Distributed Lag (ARDL) bound testing approach to co-integration to examine the existence of long-run relationship; error-correction mechanism for the short-run dynamics and Granger non-causality test to test the direction of causality.

The co-integration test confirms a long-run relationship between financial development and poverty reduction for India. The ARDL test results suggest that financial development and economic growth reduces poverty in both long run and short run. The causality test confirms that there is a positive and unidirectional causality running from financial development to poverty reduction.

This study implies that poverty in India can be reduced by financial inclusion and financial accessibility to the poor. For a fast growing economy with respect to financial sector development this may have far-reaching implication toward inclusive growth.

This paper is the first of its kind to empirically examine the causal relationship between financial sector development and poverty reduction in India using modern econometric techniques.

The purpose of this paper is to examine the relationship between financial development indicators and human development in India using annual data from 1980-2012.

The Ng-Perron unit root test is used to check for the order of integration of the variables. The long run relationship and short run dynamics are examined by implementing the ARDL bounds testing approach to co-integration. Granger’s non-causality test and variance decomposition techniques are also used to examine the impact of financial development indicators on human development.

The results confirm a long run relationship among the variables. The results of granger non causality indicate that unidirectional causality runs from financial development indicators to human development index (HDI). The variance decomposition analysis shows that among all the financial indicators, broad money supply (M3) has the largest contribution to changes in human development in India.

The present study recommends for appropriate reforms in financial market to attain sustainable human development in India. The findings will be useful for India’s policy makers, in order to maintain the parallel expansion of financial development and human development.

This paper is first of its kind to empirically examine the casual relationship between financial development indicators and human capital development proxied by HDI in India by using modern econometric techniques.

The main purpose of the present research is to analyze the relationship between technological development, financial development and economic growth in India in a non-linear and asymmetric framework.

The study employs the nonlinear autoregressive distributed lags model (NARDL) and Hetemi J asymmetric causality tests to explore nonlinearities in the dynamic interaction among the variables. The stationarity properties of data are checked by using Ng–Perron and ADF structural break unit root tests. The unit root test confirms that the variables are non-stationarity in level and are differenced stationary.

The study finds that there is a cointegrating relationship between technological development, financial development and economic growth in the long run. The findings suggest that a positive shock in technological development increases economic growth (coefficient value 1.497 at 1% significance level) and a negative shock will harm economic performance (coefficient value −0.519 at 1% significance level). A long-term positives shock in financial development boosts the economy (coefficient value 1.08 at 5% significance level) and negative shock hampers the economic performance (coefficient value −1.09 at 5% significance level). The asymmetric causality test result confirms bi-directional causality between technological development and economic growth and unidirectional causality from negative economic growth to negative technological development and bi-directional causality between economic growth and financial development, unidirectional negative financial development to economic growth.

The results of this research can significantly facilitate stakeholders and policymakers in devising short-term as well as long-term policies for financial development and technological innovation to achieve sustainable long-run economic growth in India.

This paper is the first of its kind to empirically examine the cointegrating and causal relationship between technology, financial development and economic growth in India using non-linear asymmetric cointegration and causality tests.

The purpose of this paper is to investigate firm strategies and the exertion of market power in the brewing sector in Brazil following a merger between the two largest brewers (Brahma and Antarctica) that created Ambev and given that the existing literature is inconclusive on this subject

In this study the authors apply cointegration analysis to price series of beer brands. The authors use the reduced form vector error correction (VEC) model to measure the price responses of beer brands in terms of direction, magnitude and speed. The authors use monthly retail prices for the primary brands of beer in the city of São Paulo, Brazil's largest consumer market. Specifically, the authors use two sets of retail prices, one from bars (the main point of beer sales, with roughly 50% of market share) and another from supermarkets. The series range from 1994 to 2014, depending on the brand.

This study indicates that Ambev's two major brands (Skol and Brahma) behave as market leaders, while its third brand (Antarctica) has been used to challenge the low-price competitor (Nova Schin). The authors also found evidence that the pricing policies of Brahma and Antarctica have changed toward cooperation following the creation of Ambev.

The main limitation of this article is that the authors only had access to retailer data. As the merger involved brewers, the authors would ideally use manufacturer beer prices in their econometric analysis. However, the consistency of our results suggests that retailers have been passively transmitting brand strategies launched at a manufacturer level.

As the dominant firm created following the merger of the two largest brewers appears to use one of its brand to restrict entry of competitors and the premium brands to enjoy high profits, consumers tend to be harmed by high beer prices and lack of options. Furthermore, small and medium-size companies cannot grow due to entry barriers created by the dominant firm.

This paper is the first to apply cointegration analysis to examine the effect of mergers on pricing strategies. The robustness of this study suggests that this approach could be used for antitrust agencies to monitor post-merger strategies.

This paper aims to examine the relationship between commercial bank lending and business cycle in South Africa. This paper attempts to know whether commercial bank lending in South Africa is procyclical.

The model assumed that the lending behaviour is related to the business cycle. In this study, vector error correction model (VECM) is used to capture the relationship between bank lending and business cycle to accurately elicit the macroeconomic long-run relationship between business cycle and bank lending, as some banks might slow down bank lending due to some idiosyncratic factors that are not related to the downturn in the economy. This paper uses data from South African Reserve Bank for the period of 1990-2015 using VECM to understand the extent to which business cycle fluctuation can affect credit crunch in the financial system. The Johansen cointegration approach is used to ascertain whether there is indeed a long-run co-movement between credit growth and business cycle.

Results from the VECM show that there are significant linkages among the variables, especially between credit to gross domestic product (GDP) and business cycle. The influence of business cycle is seen vividly after a period of four to five years, where business cycle explains 20 per cent of the variation in the credit to GDP. South African banks tend to change their lending behaviour during upturns and downturns. This result further confirms the assertion in theory that credit follows business cycle and can amplify credit crunch. The result shows that in the long run, fluctuations in the business cycle can influence the credit growth in South Africa.

The impulse analysis result shows that the impact of business cycle shock is very persistent and lasting. This also demonstrates that the shocks to the business cycle result have a persistent and long-lasting impact on credit. This study finds that commercial bank lending in South Africa is procyclical. It is suggested that the South African economy needs forward-looking policies that will mitigate the flow of credit to the real sector and at the same time ensure financial stability.

Most research papers rarely distinguish between the demand side and supply side of credit procyclicality. This report is presented to develop an econometric model that will examine demand side procyclicality. This study adopts more realistic and novel methods that will help in explaining the relationship between bank lending and business cycle in South Africa, especially after the global financial crisis. This report is presented with a concise and detailed analysis and interpretation.