The saving and investment nexus as postulated by Feldstein and Horioka (FH) (1980) is revisited. The saving investment correlation for China is estimated over the periods 1952-1998 and 1952-1994, the latter culminating in a period of fixed exchange rate regime. Amongst the key results, it is found that saving and investment are correlated for China for both the period of the fixed exchange rate and the entire sample period. With high saving-investment correlation, the results suggest that the Chinese economy is in conformity with the FH hypothesis. This is a valid outcome, for in China capital mobility was fairly restricted over the 1952-1994 period as indicated by the relatively low foreign direct investment.

In this paper, we propose a new augmented Dickey-Fuller-type test for unit roots which accounts for two structural breaks. We consider two different specifications: (a) two breaks in the level of a trending data series and (b) two breaks in the level and slope of a trending data series. The breaks whose time of occurrence is assumed to be unknown are modeled as innovational outliers and thus take effect gradually. Using Monte Carlo simulations, we show that our proposed test has correct size, stable power, and identifies the structural breaks accurately.unit root test, multiple structural breaks, break date estimation, Monte Carlo simulations, US macroeconomic variables,

As the coronavirus pandemic (COVID-19) has amplified so has country responses to it. With COVID-19 taking its toll on humans, as reflected in the number of people infected by, and deaths from, COVID-19, countries responded by locking down economic activity and peoples movement, imposing travel bans, and implementing stimulus packages to cushion the unprecedented slowdown in economic activity and loss of jobs. This article provides a commentary on how the most active financial indicator-namely, the stock price-reacted in realtime to different stages in COVID-19's evolution. We argue that, as with any unexpected news, markets overreact and as more information becomes available and people understand the ramifications more broadly the market corrects itself. This is our hypothesis which needs robust empirical verification.

Highlights We examine the effect of government responses of G7 countries to COVID-19. We focus on reaction of G7 stock market returns. We show the importance of lockdowns, travel bans, and economic stimulus. Lockdowns resulted in cushioning the effects of COVID-19 most.

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This paper examines the short-run and long-run relationships between visitor arrivals in Fiji, real disposable incomes and relative hotel and substitute prices for the period 1970–2000, using cointegration techniques and error correction models. The paper uses a cointegration technique – the bounds testing approach developed within an autoregressive distributed lag (ARDL) framework – that has not previously been used to estimate tourism demand models. The main advantage of the approach is that, apart from providing robust results in small sample sizes, it needs no a priori knowledge about the integration properties of the variables. The long-run results indicate that growth in income in Fiji's main tourist source markets has a positive impact on visitor arrivals while relative hotel and substitute prices have negative impacts on visitor arrivals. The findings are consistent with economic theory and proffer important policy implications.