Journal de l'économie mondiale

The COVID-19 pandemic has affected the global economy in different ways. While some sectors such as aviation and tourism experienced a sharp decline in demand, others felt some growth. For example, the media and food retail industry are some of the sectors that have benefitted from the pandemic. They experienced a rise in demand for products and services as lockdowns and other measures to reduce the spread of the coronavirus forced people to remain at home and use online channels for entertainment and to order goods. Nevertheless, the COVID-19 pandemic has severely affected the globalization of consumption by lowering people's incomes and reducing the demand for goods and services. It indicates the need for governments to use a fiscal policy that involves changes to taxes and higher spending to boost people’s incomes and trigger growth through higher consumption. Thus, the economic challenges of the COVID-19 pandemic have caused a decline in the globalization of consumption but a fiscal policy will be useful in overcoming the problems and enabling nations to resume growth.

The world has witnessed several financial crises directly affected the economic growth rates and contributed to the impact of the main indicators of this growth starting from the Great Depression 1929 followed by the Second World War, the Bretton Woods crisis, October 1973 war, the 1987 and 1989 crisis, the Second Gulf War and the Asian Tigers crisis 1998 and the mortgage crisis 2005-2007. The study aims to establish the determinants and foundations of financial crises, as they are all similar in their timing almost every decade once and accompanied by an economic bubble in a particular sector of the economy such as the industrial sector in 1929, the oil industry 1973, the financial sector 1998 and the real estate sector 2008 and the end of the bubble the crisis occurs. What we are witnessing in the current year 2019 is the end of the economic cycle and a big bubble witnessed in the services and financial derivatives sector, where we can say that all crises centre on exchange rates and the lack of GDP development in proportion to the population, inflation rates, exchange rates, interest rates, stocks and the strength of Dollars as an intermediary currency for international exchanges.

The linear relationship between time series variables is normally assumed to be stationary or simply the mean and variances do not change over time and the covariance of a variable and its lagged values are constant over time. In real situations there are some major events that can influence the fluctuations of such time series variables. Structural changes can identify whether the linear relationship between independent and dependent variable changes over some time t. The main purpose of this paper is to highlight some of the major structural breaks in tobacco consumption in Kenya for the period 1980 to 2016. The data used was extracted from Kenya National Bureau of Statistics (KNBS) and Government statistical abstracts. The independent variables are the prices of tobacco both before and after tax and per capita income. The Zivot-Andrews test was applied to test one structural break, but Clement-Montane and Reyes test was used to identify the multiple structural changes. The results obtained were presented in a table form and figure for visual identification. Zivot Andrews showed that there were major and significant structural breaks in tobacco consumption in the year 2007(t-statistic value is -6.366), prices before tax in the year 1999(t-statistic value is -4.882) and per capita income had a break year 2006 (t-statistic value is -2.627). Clement Montane and Reyes results indicated that the variables under study had significant break years (p-values were less than 5 per cent significance level). Based on the results obtained, the consumption of tobacco had two major break structural breaks in the year, 1994 and 2003, similarly the income per capita break years were 1999 and 2009, also, the prices before and after-tax break years were in 1996 and 2003, and in 1995 and 2009 respectively. This structural change is an important observation in analysis as it improves the efficiency of the estimates and assist researchers and governments to identify policies that can help reduce tobacco use, reduce diseases associated with tobacco for a functional healthy nation.