The role of oil price shocks in economic activity and inflation is a controversial but key input to economic policy. To examine these relations, we employ a refined measure of oil shocks based on decomposing realized volatility and estimated using intraday oil futures data. In new results, we find that asymmetric shocks driven by oil price increases (decreases) are actually associated with rising (falling) economic activity, particularly in the US case; while a symmetric volatility channel confirms that increasing oil price volatility negatively affects economic activity, particularly for the EU. Finally, we show that the inflationary effect of rising oil prices holds not only for the US economy, but for the rest of the world.

The dynamic conditional correlation (DCC) and co-range models are two main frameworks used to incorporate range-based univariate volatility. Using the two approaches, we construct novel multivariate range-based EGARCH (REGARCH) models: a DCC-REGARCH and co-range REGARCH (CRREGARCH) model, and a co- range CARR (CRCARR) model. We compare these models with five existing models over twelve forecast horizons, ranging from one to twelve weeks, covering currencies and ETFs. Among the eight models, the DCCREGARCH and CRREGARCH models show the best performance in out-of-sample forecasting of the variance- covariance matrix across a range of market conditions and forecast horizons. These models also generate the lowest variance and turnover for global minimum-variance (GMV) portfolios in the majority of cases.

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In this paper we empirically examine the impact of oil price uncertainty shocks on US stock market volatility. We define the oil price uncertainty shock as the unanticipated component of oil price fluctuations. We find that our oil price uncertainty factor is the most significant predictor of stock market volatility when compared with various observable oil price and volatility measures commonly used in the literature. Moreover, we find that oil price uncertainty is a common volatility forecasting factor of S&P500 constituents, and it outperforms lagged stock market volatility and the VIX when forecasting volatility for medium and long-term forecasting horizons. Interestingly, when forecasting the volatility of S&P500 constituents, we find that the highest predictive power of oil price uncertainty is for the stocks which belong to the financial sector. Overall, our findings show that financial stability is significantly damaged when the degree of oil price unpredictability rises, while it is relatively immune to observable fluctuations in the oil market.

In this paper, we empirically examine the predictive power of oil price uncertainty on time-varying volatility in the oil futures market. Quantifying oil price uncertainty as the purely unforecastable component of oil price changes, we find this measure has significant predictive power on the return volatility of crude oil futures for horizons up to 9 months ahead. Moreover, our oil price uncertainty factor outperforms the realized oil price volatility. In addition, our structural vector autoregression model shows that the effect of oil price uncertainty shock on oil-market volatility is higher in magnitude and persistence when compared with the effect of aggregate demand, oil demand, supply, and oil price volatility shocks.

This paper investigates the nexus between women's empowerment and child health, in particular examining whether having more rights, and which rights, leads to improvements in the well-being of children, as reflected by child mortality rates. We distinguish between civil rights, political rights, and economic rights. In our sample of 134 countries over the period 1950-2018, and employing 27 separate rights-based measures of empowerment, women's empowerment commonly contributes to a reduction in child mortality in high-income countries, however, low- and middle-income countries reveal striking differences across some measures. For example, while women's participation in public administration or employment in the public sector is associated with reduced child mortality, the opposite is observed for the right to run a business and access to banking. Results suggest that strong institutions are needed to ensure rights are translated into better welfare.

Focusing on the most liquid segment of the European CDS market, this paper studies the impact of key standardization reforms. We document that the introduction of an upfront fee to standardize the cash flow of CDS contracts created an initial capital cost for traders, leading to higher CDS prices. This relation holds after accounting for well-known determinants of spreads, suggesting a separate funding channel driven by the greater capital intensity of trading. This effect is stronger when dealers are likely to bear the initial capital cost and is present across all industries, except for swaps written on financials.

Investor behaviour in a crisis can amplify, or ameliorate, shocks and may alter in response to government policy. To investigate, we assess whether Private Equity (PE) and Venture Capital (VC) responded to the paycheck protection program (PPP) – the primary vehicle the US Federal government employed to support SMEs during the Covid-19 pandemic. Matching large PE/VC and PPP datasets, we create a unique database that identifies 4,240 PPP loan-holding portfolio firms. We use a difference-in-difference approach and show a greater likelihood of a PE or VC buyout deal for firms with PPP loans. Smaller PE players – which earlier work suggests are vulnerable to systemic shocks - seem to have been particularly active.

While financial development is often found to raise income inequality, it remains unclear whether the composition of the financial system makes a difference. In our sample of 99 countries over the period 1975–2020, increased activity of banks relative to markets in the provision of financial services is robustly associated with less inequality in the developing world yet with more inequality in developed economies. Accounting for redistribution systems does not alter this finding; banking sector concentration amplifies the effects. Results suggest that banks work at the extensive margin at earlier stages of economic development yet shift to the intensive margin at higher levels of development, where they increasingly serve the interests of the rich. Higher market power enables banks to better pursue their objectives at each of the margins.

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The sheer scale of the current environmental challenge underscores the need for successful generation and application of environmentally sustainable innovations. At the same time, there has been growing interest in how national institutional contexts interact with the financial ecosystem, corporate governance, and firm behaviour. Bringing these topics together, we theoretically address and empirically evaluate the institutional and financial conditions under which green innovation and application occur. Using a novel sample of 53 countries over a twenty-one-year period, we show that green innovation is more likely to occur in Liberal Market Economies, a crucial feature of which is the heavier reliance by firms on markets to obtain their finance. However, we also show that this innovation is applied more frequently in economies with a higher degree of State coordination and where high short-term returns are less in demand. Given national institutional contexts are persistent, our results highlight that extensive regulatory intervention is likely required to develop green economies.

We explore how information additional to a specific price series can be used to improve the power of popular univariate autoregressive-based methods for detecting and dating speculative price bubble episodes. Following Phillips et al. (2011, 2015) we base our approach on sequences of sub-sample regression-based augmented Dickey-Fuller [ADF] statistics. Our point of departure from these extant procedures is to allow for additional information in the testing and dating procedures. To do so we follow the approach of Hansen (1995) and augment the sub-sample ADF regressions with covariate regressors. The limiting null distributions of the resulting statistics depend on the long-run squared correlation between the covariates and the regression error. We show that this dependence can be accounted for by using a residual bootstrap re-sampling method. Simulation evidence shows that including relevant covariates can significantly improve the efficacy of both the resulting bubble detection tests and the associated date-stamping procedure, relative to using standard sub-sample ADF statistics. An empirical application of the proposed methodology to monthly S&P 500 data is considered, using a variety of candidate covariates. Using these covariates, the onset of the dotcom bubble and the bubble associated with Black Monday are both identified significantly earlier than when using standard methods.

Despite the important impact of commodity terms-of-trade (CTOT) on GDP growth, child mortality rates and public debt, little is known about its determinants. Using data from 178 countries (grouped according to their commodity export-import structure) over the period 1962 to 2020, we examine the short-and long-run effects of global economic activity, OECD and emerging markets growth, the exchange rate of U.S. dollar, stock price volatility and real interest rates on CTOT growth. We demonstrate their typical asymmetric effect on exporters and importers, and show, for example, that the exchange rate of the U.S. dollar also exhibits opposite effects over the short and long run due to inelastic commodity demand. We find that the growth of emerging market economies provides the most universal and consistent effect across all of our subsamples (i.e., energy and non-energy exporters and importers) - this latter point underscores the contemporary global importance of developing countries' growth.

Given uncertainty in policy, particularly around Brexit, how do private equity (PE) firms investing in the UK behave? Analysing their response is vital for understanding the impact on investment per se and designing policy that limits uncertainty. Building on the recent work of Mike Wright and co‐authors, we explore the effect of uncertainty measures on UK PE activity and the channels that transmit uncertainty to the PE market. After developing hypotheses that link the ‘PE activity and uncertainty’ relation via a real options, interim risk or moral hazard channel, we employ a novel dataset on PE targets and non‐targets over the 2010–2019 period. We find that uncertainty, especially new measures closely aligned to Brexit, have negatively affected PE activity in the UK. Moreover, the transmission of such uncertainty occurs primarily through the real options channel and through greater uncertainty arising from prolonged interim periods of PE deals (i.e. the interim risk channel). Our results imply that the present and ongoing uncertainty in Brexit policy will continue to depress PE activity and by extension, investment and growth in the UK. Policymakers are urged to resolve such uncertainties.

This paper develops a stylised model for S&P 500 index changes with two beta-based styles: index trackers and beta arbitrageurs who trade in both high and low beta event stocks to exploit mean reversion towards one. Arbitrageurs engage in common or contrarian trading patterns relative to index funds depending on whether historical betas are below or above one. Thus, the overall comovement effect has two distinct components. After index additions, pre-event low beta stocks drive the overall beta increases due to common demand – albeit for different reasons - from indexers and arbitrageurs. By contrast, arbitrageur shorting of high beta additions diminishes or sometimes reverses the beta increases for these stocks driven by indexers. Analogous results hold for index deletions.

This paper explores how the 2016 US Prime Money Market Funds (PMMFs) regulation affected the crude oil market. This reform led to an increase in short-term dollar borrowing costs and the oil sector became particularly susceptible to disruptions in the global funding market due to a post-financial crisis debt expansion which far outpaced other commodity industries. Building on the global crude oil market SVAR model pioneered by Kilian and Murphy (2014), we find that tighter PMMFs funding conditions have a lagged negative effect on the real price of crude oil and a lagged positive effect on oil production. We show that these responses are driven primarily by a fall in certificates of deposits issued by global banks. Lastly, we evidence that the US nominal effective exchange rate acts as a transmission channel for the negative funding shock to the real price of oil.@ 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

A new method is proposed to estimate the long-term seasonal component by a multistage optimization filter with a leading phase shift (MOPS). It can be utilized to provide better predictions in case of the seasonal component autoregressive (SCAR) model, where data are filtered/decomposed into trend and remainder components and then forecasts for constituent components generated separately and later combined. This reinforces the importance of trend estimation filtering/decomposition methods, which are scarce and only few methods, primarily wavelet decomposition, have improved upon the forecasts generated by statistical linear models. We contribute to the literature by introducing a new trend estimation method, and the forecast results are compared with the most popular trend estimation methods, such as frequency filters, wavelet decomposition, empirical mode decomposition (EMD), and Hodrick-Prescott (HP) filter, through their performance in generating short-term forecasts for day-ahead electricity prices. Our method for trend estimation performs better in terms of providing short-term forecasts as compared with some well-known methods, and the best forecast, according to the Diebold and Mariano (1995) test, is obtained by using our MOPS filter with annual trend period length.