By Samuel Meng, Mahinda Siriwardana
This publication employs a computable basic equilibrium (CGE) version – a frequent fiscal version which makes use of real info to supply monetary research and coverage overview – and applies it to financial information on Singapore’s tourism undefined. The authors got down to reveal how a amateur modeller can collect the required abilities and data to effectively follow common equilibrium types to tourism experiences. The chapters clarify tips to construct a computable common equilibrium version for tourism, the way to behavior simulation and, most significantly, tips to examine modelling effects. This utilized research acts as a modelling publication at either introductory and intermediate degrees, particularly concentrating on scholars and researchers who're drawn to and need to benefit computable basic equilibrium modelling. The authors supply insightful research of Singapore’s tourism and supply either scholars and researchers with a advisor on find out how to observe basic equilibrium types to real fiscal info and draw exact conclusions.
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Extra resources for Assessing the Economic Impact of Tourism: A Computable General Equilibrium Modelling Approach
Sample text
1998; Breuss and Steininger 1998; Berrittella et al. 2004), carbon emissions (Ahammad et al. 2001; Farmer and Steininger 1999; Zhang 1998; Edwards and Hutton 2001; Gottinger 1998), pollution abatement (Dellink et al. 2004; Hyman et al. 2002; Scrimgeoura et al. 2005), and water policy (Seung et al. 2000; Stringer 2001). CGE modelling can be applied to many other areas. For example, Massey (2001), McGregor et al. (1995), De Santis (2003), and Fidrmuc (2004) used CGE models to analyse the migration phenomenon; Batey and Madden (1999) evaluated the employment impact of demographic 1 An Introduction to CGE Modelling 15 change; Acemoglu and Verdier (Acemoglu and Verdier 1998) investigated the relationship among property rights, corruption, and the allocation of talent; Carlstrom and Fuerst (1997) were interested in the relationship between agency costs, net worth, and business fluctuations; Chisari et al.
5 for all S1(c,s,i) when the value for coefficient V1PUR_S(c,i) is zero, so that the dividing-by-zero problem is avoided. The command in the last line cancels out the default setting so that the zerodivide setting will not interfere with other level equations or formulas. For a linear (or percentage change) equation, the dividing-by-zero problem can be avoided by adding a coefficient or a function. 00000000001. When you suspect there may be a dividing-by-zero problem in an equation, you can add this coefficient to that equation.
The curve in Fig. 1 represents the non-linear function and the straight line stands for the estimation of Johansen linearization. If the change of variable X is large (shown as dX in the figure), the Johansen 2 Useful CGE Modelling Packages 29 Y YJ Johansen linearizaƟon YA Nonlinear dY Y0 dX O Fig. 1 X0 XA X Johansen linearization error estimation will predict a large change in Y (dY in the figure), while the actual change is fairly small (YA À Y0). The estimation error (YJ À YA) is obviously not acceptable.