This paper seeks to revisit the highly debated trade‐growth hypothesis by considering the effects of trade and output volatility on the relationship between trade and…
This paper seeks to revisit the highly debated trade‐growth hypothesis by considering the effects of trade and output volatility on the relationship between trade and economic growth.
The relationship is modeled by testing for the existence of output and trade (export and imports separately) using the conditional variances of the variables and then specifying an autoregressive conditional heteroskedastic (ARCH) process in a vector error correction model.
Using Singapore as a case study, the paper finds the two‐way relationship between export growth and trade‐adjusted GDP growth is robust even after controlling for the effects of income and export volatility. In addition, neither trade nor GDP volatility bears any impact on the bi‐directional causality between imports and unadjusted GDP growth thereby highlighting the crucial role of imports as intermediate inputs and embodying foreign technology in promoting economic growth. There is also evidence that output volatility impedes output and trade growth, while trade volatility exerts a negative influence on the trade‐adjusted income growth.
Ignoring the presence of trade and output volatility in modeling the trade‐growth relationship provides biased empirical results which have serious implications for trade‐oriented growth strategies that policy makers cannot afford to ignore.
This is the first attempt to explicitly model output, export and import volatility in empirically testing the trade‐growth hypothesis. Second, the robustness of the hypothesis is also tested by considering GDP and non‐trade GDP as it has been argued that use of GDP may lead to the problems of simultaneity and specification bias since exports and imports are themselves a component of GDP.
Although an East Asian miracle, Singapore has been singled out for experiencing insignificant total factor productivity (TFP) growth, thereby reflecting limited potential…
Although an East Asian miracle, Singapore has been singled out for experiencing insignificant total factor productivity (TFP) growth, thereby reflecting limited potential for long‐term growth. Examines the validity of this statement for the services sector, which is an important engine of growth for Singapore. This is done using panel data with a stochastic frontier model, which, unlike the conventional growth accounting model used by previous studies, not only decomposes output growth into input growth and TFP growth but further decomposes TFP growth into technological progress and changes in technical efficiency. In addition, the stochastic frontier model incorporates the more realistic non‐neutral shifting production frontier, as opposed to the commonly assumed Hicks‐neutral production technology underlying a production function.
This paper seeks to examine the impact of various socio‐economic factors on the viability of sugar production by focusing on the technical efficiency of farm performance.
The examination is undertaken by empirically estimating the random coefficient production frontier using farm level data. The paper uses Fiji as a case study.
In general, farmers produced 25 per cent less than their potential output. Among the farm inputs, land (labour) was the most (least) efficiently used input. Empirical evidence also suggests that large‐scale farming should be seriously considered by amalgamating land leases. Lastly, sugar reform can be successful with the use of appropriate best farming techniques to improve cane yield, and if there is successful expansion of sugar‐related products.
This is the first attempt to estimate the random coefficient frontier model that enables the examination of overall technical efficiency of the farm as well as input‐specific technical efficiency for improved policy formulation.