Inflation and infrastructure sector returns in emerging markets—panel ARDL approach

Magweva, Rabson; Sibanda, Mabutho

doi:10.1080/23322039.2020.1730078

Cited by 19 publications

(14 citation statements)

References 27 publications

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“…Their study also offers substantial portfolio diversification benefits with all assets. However, Magweva and Sibanda (2020) did not find inflation hedging benefits of infrastructure sector returns in emerging markets. It is suggestive of the existence of significant beta risk in emerging stock markets.…”

Section: Literature Reviewmentioning

confidence: 94%

Infrastructure Equity and Firm Performance in India

Hasnat

2020

Millennial Asia

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The growing financing requirements coupled with tightening of fiscal purse strings point to the pertinence of market-based finance for infrastructure provision and enhancement. For this, the question of the sectoral performance of infrastructure takes centre stage and this becomes the basis for the present study. The study assesses the risk-return and volatility profile of Nifty Infra, the National Stock Exchange (NSE) sectoral index for the 30 biggest infrastructure firms in India vis-à-vis the broader Nifty 50 for the time period 2010–2018. The study employs the standard financial economic analysis methods of capital asset pricing model (CAPM) and generalized autoregressive conditional heteroskedasticity in mean (M-GARCH) model and finds the sectoral equity performance of infrastructure to be marginally below that of a broadly diversified index. Further, the study analyses the cash flow and leverage characteristics which are imperative factors in medium-term risk-return profile of infrastructure stocks. The disaggregated firm level analysis of 10 select firms reveals that rent-like return does exist for the biggest players in the sector due to past installed capacities, while the subcontracting mechanism percolates to meagre cash flows for smaller players, partly bearing the greenfield risks. This suggests the need for state-induced measures to prop up liquidity in equity trade for infrastructure firms. This would not only enhance the risk-return profile but also mitigate excessive volatility for these heavily leveraged firms.

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Section: Literature Reviewmentioning

confidence: 94%

Infrastructure Equity and Firm Performance in India

Hasnat

2020

Millennial Asia

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“…PMG also provides consistent coefficients despite the possible presence of endogeneity because they include the lags of dependent and independent variables. The PMG is a more middle-of-the-road approach to heterogeneous panel data estimation than Mean Group (MG) and Dynamic Fixed Effect (DFE) specification (Magweva & Sibanda, 2020).…”

Section: Methodsmentioning

confidence: 99%

“…Moreover, panel estimation decreases the noise that comes from individual time-series estimation. This leads to a more reliable inference (Attard, 2019;Magweva & Sibanda, 2020). Additionally, ARDL has the advantage in the mixed integration level of first difference (I(1)) and level (I(0)) as well as purely I(0) or I(1).…”

Section: Literature Reviewmentioning

confidence: 99%

Projection of Indonesian Islamic commercial banks efficiency and stability in the Covid-19 period using DEA and panel ARDL

Himmawan

Firdausi

2021

JEKI

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Purpose -This study aims to assess the efficiency and stability of Indonesia Islamic Commercial Banks, and then the results are used as a projection in the Covid-19 period. It uses the sample from 14 Islamic Commercial Banks in Indonesia and its quarterly data from 2017 to 2020.Methodology -The DEA method analyses VRS and CRS scale using output orientation. The Panel ARDL also uses two models from the specifications in DEA, with the inputs as independent variables and the outputs as dependent variables.Findings -The result of DEA is visualized in four quadrants from each CRS and VRS model. Respectively in each model, 1 and 5 banks are highly efficient and stable, 5 and 2 banks have high efficiency but low stability, 4 and 2 banks have low efficiency but high stability, 4 and 5 banks have low efficiency and stability. In the Panel ARDL, third party fund, operational expenses, and total financing have significant and stable long-run effect in both models. In the short-run, only operational expenses significantly affect operational earnings, whereas only total financing significantly affects total assets.Practical implications -Banks may use strategies such as absorbing workforces as marketing representatives, utilizing cooperative agreements, crowdfunding, improving banking technology, creating provisions on expected credit loss, and deferring profit.Research limitations -The limitation of this study is the small sample size because only 14 Islamic commercial banks are used as the sample, without considering the Islamic business units of the conventional banks so the predictive strength of the result only constrained in the Islamic commercial banks.Originality -The study uses two different methods in assessing Islamic Commercial Banks especially in the Covid-19 period, hence adding insights on Islamic Commercial Banks in the pandemic period and further contributes to the Islamic banking field of study.

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“…Yatay kesit bağımlılığına sahip ve eğim heterojenliği özelliği gösteren farklı düzeyde durağan olan seriler arasındaki uzun ve kısa dönemli ilişkinin tespit edilmesinde ise Mallick vd. (2016), Magweva & Sibanda (2020) gibi çalışmaların yöntem kısımları takip edilerek Panel ARDL testinden faydalanılmıştır. Panel ARDL yöntemi, Pesaran vd.…”

Section: Veri Model Ve Yöntemunclassified