Demographic transition,education and economic growth in Tunisia

This paper provides empirical evidence supporting the interaction between fertility, education and economic growth through the underlying mechanism behind that correlation in accordance with Becker's theory. In consistency with the theory, the key explanatory variables in Tunisia's fertility model are real GDP per capita, infant mortality, contraceptive use ratio, and education. As opposed to most empirical works, the present study takes into consideration three educational levels, i.e., primary, secondary and higher. Also unlike most empirical research, this study attempts to analyse the impact of fertility transition on education and economic growth. To deal with too little or incomplete data, time series data for Tunisia are computed over 45 years. A multivariate cointegration analysis is carried out and shows that a long-term triangular relationship exists. A short dynamic run analysis based on the vector correction error model displays results in coherence with and close to those of the long term. Among our key results, education is found to trigger fertility transition both in the short and long run. In addition, education has relatively fostered economic growth but hardly boosted it through its dynamic interaction with fertility. Furthermore, the variance decomposition and the impulse function show that the fertility transition has produced a feedback effect on both education and economic growth.     

Rental housing for a French taxpayer: are there tax arbitrage opportunities in the USA?

The aim of this paper is to identify tax arbitrage opportunities in the field of rental housing in France and the USA. We conducted tax simulations for investments made in the USA or France. We compared total net rental incomes, capital gains and present investment values based on different tax regimes. Our results show that rental housing in the USA under the Effectively Connected Income classification serves as the best option, as it generates the highest present investment value. We performed several robustness exercises and we showed that our results are strengthened in cases of stronger price appreciation in the USA than in France and in cases of high landlord tax brackets.     

Multivariate volatility forecasts for stock market indices

Volatility forecasts aim to measure future risk and they are key inputs for financial analysis. In this study, we forecast the realized variance as an observable measure of volatility for several major international stock market indices and accounted for the different predictive information present in jump, continuous, and option-implied variance components. We allowed for volatility spillovers in different stock markets by using a multivariate modeling approach. We used heterogeneous autoregressive (HAR)-type models to obtain the forecasts. Based an out-of-sample forecast study, we show that: (i) including option-implied variances in the HAR model substantially improves the forecast accuracy, (ii) lasso-based lag selection methods do not outperform the parsimonious day-week-month lag structure of the HAR model, and (iii) cross-market spillover effects embedded in the multivariate HAR model have long-term forecasting power.     

Investigating first‐stage exchange rate pass‐through: Sectoral and macro evidence from euro area countries

In this paper, we evaluate the first‐stage pass‐through, namely the responsiveness of import prices to the exchange rate changes, for a sample of euro area (EA) countries. Our study aimed to shed further light on the role of microeconomic factors versus macroeconomic factors in influencing the extent of the exchange rate pass‐through (ERPT). As a first step, we conduct a sectoral analysis using disaggregated import prices data. We find a much higher degree of pass‐through for more homogeneous goods and commodities, such as oil and raw materials, than for highly differentiated manufactured products, such as machinery and transport equipment. Our results confirm that cross‐country differences in pass‐through rates may be due to divergences in the product composition of imports. The higher share of imports from sectors with lower degrees of pass‐through, the lower ERPT for an economy will be. In a next step, we investigate for the impact of some macroeconomics factors or common events experienced by EA members on the extent of pass‐through. Using the system generalised method of moments within a dynamic panel‐data model, our estimates indicate that decline of import‐price sensitivity to the exchange rate is not significant since the introduction of the single currency. Our findings suggest instead that the weakness of the euro during the first 3 years of the monetary union significantly raised the extent of the ERPT. This outcome could explain why the sensitivity of import prices has not fallen since 1999. We also point out a significant role played by the inflation in the Eurozone, as the responsiveness of import prices to exchange rate fluctuations tends to decline in a low and more stable inflation environment. Overall, our findings support the view that the extent of pass‐through is comprised of both macro‐ and microeconomic aspects that policymakers should take into account.     

Central Bank Currency Swaps and the International Monetary System

Central bank currency swaps have emerged as a de facto key feature of the international monetary system, with the US Federal Reserve having extensive recourse to them during the financial crisis, and their exploitation by the People’s Bank of China to help internationalizing the renminbi. Combined with the unlimited and exclusive power of central banks to create money these swaps can match the volatility of international capital flows. However, they have so far not been associated with conditionality, and are more precarious than alternative institutional arrangements. Strictly framing the discretionary use of this tool seems unrealistic but an internationally agreed set of principles would enable a fairer and perhaps more efficient exploitation of this instrument.     

Robust estimation of intraweek periodicity in volatility and jump detection

Opening, lunch and closing of financial markets induce a periodic component in the volatility of high-frequency returns. We show that price jumps cause a large bias in the classical periodicity estimators and propose robust alternatives. We find that accounting for periodicity greatly improves the accuracy of intraday jump detection methods. It increases the power to detect the relatively small jumps occurring at times for which volatility is periodically low and reduces the number of spurious jump detections at times of periodically high volatility. We use the series of detected jumps to estimate robustly the long memory parameter of the squared EUR/USD, GBP/USD and YEN/USD returns.     

Do banks overstate their Value-at-Risk?

This paper is the first empirical study of banks’ risk management systems based on non-anonymous daily Value-at-Risk (VaR) and profit-and-loss data. Using actual data from the six largest Canadian commercial banks, we uncover evidence that banks exhibit a systematic excess of conservatism in their VaR estimates. The data used in this paper have been extracted from the banks’ annual reports using an innovative Matlab-based data extraction method. Out of the 7354 trading days analyzed in this study, there are only two exceptions, i.e. days when the actual loss exceeds the disclosed VaR, whereas the expected number of exceptions with a 99% VaR is 74. For each sample bank, we extract from historical VaRs a risk-overstatement coefficient, ranging between 19 and 79%. We attribute VaR overstatement to several factors, including extreme cautiousness and underestimation of diversification effects when aggregating VaRs across business lines and/or risk categories. We also discuss the economic and social cost of reporting inflated VaRs.     

On the properties of high-order non-monetary measures for risks

This paper investigates how welfare losses for facing high-order risk increases change when the risk environment of the decision maker is altered. To that aim, we define the nth-order utility premium as a measure of pain associated with facing the passage of one risk to a more severe one and we examine some of its properties. Changes in risk are expressed through the concept of stochastic dominance of order n. The paper investigates more particularly welfare changes of merging increases in risk, first ignoring background risks, then taking them into account. Merging increases in risk may be beneficial or not, depending on whether background risks are considered and how. The paper also provides conditions on individual preferences for superadditivity of the nth-order utility premium. The results confirm the importance and usefulness of two analytical concepts: mixed risk aversion and risk apportionment.     

Stock selection using a multi-factor model - empirical evidence from the French stock market

Using a Barra-type factor model, we have attempted to determine whether it is possible to beat the benchmark by taking advantage of anomalies established in the financial empirical literature. More specifically we have built an equity premium model based on three sets of factors (accounting variables, stock market characteristics and sector indicators) using a Bayesian method corrected for heteroscedasticity to estimate risk premiums, a technique that takes agents' learning into account. The results are encouraging: first, the factors that carried most weight on the equity premiums corroborated the results of empirical studies described in the financial literature, secondly, the portfolios constructed from our methodology and simulated outside our sample, returned higher performance than the benchmark and rewarded the supplement of volatility.