New Findings on Key Factors Influencing the UK's Referendum on Leaving the EU

The UK’s EU in/out referendum raised significant debate and speculation of the intention of the electorate and its motivations in voting; much of this debate was informed by simple data analysis examining individual factors, in isolation, and using opinion polling data. This, in the case of the EU referendum where multiple factors influence the decision simultaneously, failed to predict the eventual outcome. On June 23, 2016, Britain’s vote to leave the EU came as a surprise to most observers, with a bigger voter turnout than that of any UK general election in the past decade. In this research, we apply multivariate regression analysis and a Logit Model to real voting data to identify statistically significant factors influencing the EU referendum voting preference simultaneously as well as the odd ratio in favor of Leave. Visualizations of the key findings are also provided with heat maps and graphs. We find that higher education is the predominant factor dividing the nation, with a marginal effect on the referendum decision being stronger than any other factors particularly in England and Wales, where most Leave voters reside. An increase of about 3% in the proportion of British adults accessing to higher education in England and Wales could have reversed the referendum result in the UK. We also find that areas in England and Wales with a lower unemployment rate tend to have a higher turnout to support Leave while areas in Scotland and Northern Ireland with a higher proportion of university-educated British adults have a higher turnout to support Remain. Further we find that areas with high proportions of British male adults show a higher percentage of Leave votes. A higher proportion of elderly British contributes to a higher percentage of Leave votes, but does not lead to Leave outcomes on their own

What could have tipped the EU referendum result in favour of Remain

[First paragraphs] Much of the analysis about why the UK voted to leave the European Union in June 2016 has been done by looking at individual factors in isolation, or using opinion poll data from both before and after the vote. In a new research paper, I applied two statistical analyses to the actual referendum voting data obtained from the Electoral Commission and the UK’s latest census data. I found that while voters’ level of higher education was the most important factor, the gender of voters and the turnout level also had parts to play in the victory for the Leave campaign

Data for: Association and risk of arsenic-related miRNAs with arsenic-induced multi-organ damage

Data for: Association and risk of arsenic-related miRNAs with arsenic-induced multi-organ damag

On the effects of changing mortality patterns on investment, labour and consumption under uncertainty

In this paper we extend the consumption-investment life cycle model for an uncertain-lived agent, proposed by Richard (1974), to allow for flexible labor supply. We further study the consumption, labor supply and portfolio decisions of an agent facing age-dependent mortality risk, as presented by UK actuarial life tables spanning the time period from 1951-2060 (including mortality forecasts). We find that historical changes in mortality produces significant changes in portfolio investment (more risk taking), labour (de- crease of hours) and consumption level (shift to higher level) contributing up to 5% to GDP growth during the period from 1980 until 2010

On the effects of changing mortality patterns on investment, labour and consumption under uncertainty

In this paper we extend the consumption-investment life cycle model for an uncertain-lived agent, proposed by Richard (1974), to allow for flexible labor supply. We further study the consumption, labor supply and portfolio decisions of an agent facing age-dependent mortality risk, as presented by UK actuarial life tables spanning the time period from 1951-2060 (including mortality forecasts). We find that historical changes in mortality produces significant changes in portfolio investment (more risk taking), labour (de- crease of hours) and consumption level (shift to higher level) contributing up to 5% to GDP growth during the period from 1980 until 2010

Supplemental Material - The hypermethylation of <i>FOXP3</i> gene as an epigenetic marker for the identification of arsenic poisoning risk

Supplemental Material for The hypermethylation of FOXP3 gene as an epigenetic marker for the identification of arsenic poisoning risk by Lu Ma, Xiaolin Fang and Aihua Zhang in Human & Experimental Toxicology</p

On the calibration of the Schwartz two-factor model to WTI crude oil options and the extended Kalman Filter

The Schwartz (J Finance 52(3):923–973, 1997) two factor model serves as a benchmark for pricing commodity contracts, futures and options. It is normally calibrated to fit the term-structure of a range of future contracts with varying maturities. In this paper, we investigate the effects on parameter estimates, if the model is fitted to prices of options, with varying maturities and strikes instead of futures, as is commonly done. The use of option prices rather than futures in the calibration leads to non-linearities, which the standard Kalman filter approach is unable to cope with. To overcome these issues, we use the extended Kalman Filter. We find that some parameters sensitively depend on the choice of strikes of the corresponding options, and are different from those estimates obtained from using futures prices. This effect is analogue to varying implied volatilities in the Black–Scholes model. This realization is important, as the use of ill-fitted models for pricing options in the Schwartz (1997) framework may cause traders to bear serious financial losses

On the calibration of the Schwartz two-factor model to WTI crude oil options and the extended Kalman Filter

The Schwartz (J Finance 52(3):923–973, 1997) two factor model serves as a benchmark for pricing commodity contracts, futures and options. It is normally calibrated to fit the term-structure of a range of future contracts with varying maturities. In this paper, we investigate the effects on parameter estimates, if the model is fitted to prices of options, with varying maturities and strikes instead of futures, as is commonly done. The use of option prices rather than futures in the calibration leads to non-linearities, which the standard Kalman filter approach is unable to cope with. To overcome these issues, we use the extended Kalman Filter. We find that some parameters sensitively depend on the choice of strikes of the corresponding options, and are different from those estimates obtained from using futures prices. This effect is analogue to varying implied volatilities in the Black–Scholes model. This realization is important, as the use of ill-fitted models for pricing options in the Schwartz (1997) framework may cause traders to bear serious financial losses