Suchergebnisse

PurposeShanghai is the most important economic centre in China. It also has the nation's largest modern office market in terms of floorspace and investment values. However, as with office markets in other cities and countries, the Shanghai market displays rental volatility. This paper aims to examine this issue.Design/methodology/approachRental volatility is examined by econometrically constructing a long‐run equilibrium relationship between rent and underlying demand and supply side factors. In order to establish the validity of this model, it is tested for the presence of a cointegrating vector. From this a short‐run dynamic adjustment model is constructed. This is an error correction mechanism that links the short‐ and long‐run models. The impact of office vacancies, foreign direct investment, and changes in the real interest rate on the office market are explicitly considered.FindingsThe results indicate that both demand (as represented by gross domestic product (GDP)) and supply (stock) are significant determinants of rents. Space demand is found to be both price and income elastic. In the short‐run model the error correction term is significant and correctly signed. In comparison to other office markets, the Shanghai market adjusts rather slowly. Foreign direct investment is found to have a positive impact on long‐run rents and the vacancy rate is found to impact on short‐term rental adjustment.Originality/valueThe Shanghai office market is the most important in China. However, it has displayed significant rental volatility. This paper is the first to examine explicitly the rental adjustment process in this office market. The results suggest a market that is performing as expected by economic theory but which nevertheless displays relatively slow adjustment to market imbalances.

The research investigated the determinants of Pakistan's exports by using time series data from 1990-2016. Certain econometric tests were also applied to check cointegration among variables. A unit root test was used to check the stationarity of selected variables. After the stationarity of the data, a vector error correction model is used to estimate the effect of regressors, like foreign direct investment, gross domestic product, employment level, and consumption expenditures on a dependent variable, i.e. exports in the short run. The result shows the positive relationships that foreign direct investment, gross domestic product and employment level have on exports, and the adverse impact of consumption expenditures on the dependent variable. The study uses Johansen's cointegration test for the long run. The results show that all the variables are co-integrated in the long run. It is suggested that the government should encourage foreign direct investment and gross domestic product, which would help accelerate Pakistan's exports. It is also suggested that whenever policymakers provide a trade policy, in particular, in relation to exports, then the adverse effect of exchange rate depreciation, external debt burdens, taxes, sanctions and protectionism should be quantified, and necessary measures be suggested so as to minimize any repercussions.