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Introduction The response of aggregate labour supply to changes in the real wage has been a question of interest to economists for some time. For example, the notion of a backward‐bending supply curve for labour is commonly known, though not universally accepted. The question is of more than academic interest; it has direct relevance to tax policy, because an income tax in effect lowers the real wage, which is then likely to cause people to substitute out of work into leisure. This article evaluates the aggregate labour supply curve from within a household production framework and finds that, under plausible circumstances, the aggregate labour supply curve is likely to be very inelastic. (The model here actually considers only a subset of the long‐run aggregate supply of labour. Long‐run questions of fertility are not addressed here, nor is the labour force participation rate, which might vary in the short run in response to a change in the real wage. This article considers only the work effort of someone who is already in the labour force.) For a case derived below, the aggregate labour supply curve is always perfectly inelastic, meaning that for proportional changes in the tax structure, the quantity of labour supplied will not be a function of the tax rate. (Gwartney and Stroup[1] give a good overview of the traditional arguments along with their own argument that an income tax increase must reduce work effort).

This paper investigates distortions in financial statements that arise from employing capital assets. Use of historical cost depreciation tends to overstate earnings because of inflation effects, which in turn misrepresents firms' capacities to expand operations or to distribute dividends. We argue that the financial statement effects of inflation can be traced to two main sources: understated depreciation, and interest expense. Depending on a firm's capital structure choices, the distortion from historical cost depreciation is heightened or mitigated. Measurement errors in accounting numbers obscure the relation between price and earnings. We develop value relevant adjustments that enhance the informativeness of earnings. We also show that the effects of measurement errors from using historical cost depreciation are most pronounced in firms that carry lower levels of debt.

This paper presents new general mathematical models of normalized hysteresis curves, which define major‐hysteresis‐loop and minor‐hysteresis‐loop trajectories with several degrees of freedom. These mathematical models may be integrated into models of circuits containing nonlinear inductances for application in simulation studies. Also, the models presented can be applied to the description of hysteresis of different physical nature in other areas of science where the hysteresis phenomenon is encountered, for example: dielectric hysteresis, mechanical hysteresis, adsorption hysteresis, optical hysteresis, and so forth.

Gives introductory remarks about chapter 1 of this group of 31 papers, from ISEF 1999 Proceedings, in the methodologies for field analysis, in the electromagnetic community. Observes that computer package implementation theory contributes to clarification. Discusses the areas covered by some of the papers ‐ such as artificial intelligence using fuzzy logic. Includes applications such as permanent magnets and looks at eddy current problems. States the finite element method is currently the most popular method used for field computation. Closes by pointing out the amalgam of topics.

This paper proposes the Student's t Dynamic Linear Regression (St-DLR) model as an alternative to the various extensions/modifications of the ARCH type volatility model. The St-DLR differs from the latter models of volatility because it can incorporate exogenous variables in the conditional variance in a natural way. Moreover, it also addresses the following issues: (i) apparent long memory of the conditional variance, (ii) distributional assumption of the error, (iii) existence of higher moments, and (iv) coefficient positivity restrictions. The model is illustrated using Dow Jones data and the three-month T-bill rate. The empirical results seem promising, as the contemporaneous variable appears to account for a large portion of the volatility.

In empirical research, panel (and multinomial) probit models are leading examples for the use of maximum simulated likelihood estimators. The Geweke–Hajivassiliou–Keane (GHK) simulator is the most widely used technique for this type of problem. This chapter suggests an algorithm that is based on GHK but uses an adaptive version of sparse-grids integration (SGI) instead of simulation. It is adaptive in the sense that it uses an automated change-of-variables to make the integration problem numerically better behaved along the lines of efficient importance sampling (EIS) and adaptive univariate quadrature. The resulting integral is approximated using SGI that generalizes Gaussian quadrature in a way such that the computational costs do not grow exponentially with the number of dimensions. Monte Carlo experiments show an impressive performance compared to the original GHK algorithm, especially in difficult cases such as models with high intertemporal correlations.

This study focuses on the impact of internal factors, namely intrinsic motivation, ICT knowledge, and the moderating effect of demographic factors such as education level, age, gender on digital readiness of Indonesian MSMEs.

The sample data selected in this study include owners of culinary SMEs in the Salatiga area, Central Java, and who already has had a building to run their business. This study employed a quantitative approach using a statistical package to perform descriptive and inferential analyses with the help of IBM SPSS and Smart PLS.

Four hypotheses have been formulated and tested using the structured equation model. The results revealed that intrinsic motivation and ICT knowledge have a positive significant influence on the digital readiness of MSMEs.

The study concluded that the internal encouragement of the culinary MSME owners in the city of Salatiga will continue to advance and develop following the current digital technology era.

The results from the moderation testing show that women have a slightly higher average answer than men in the number of indicators of intrinsic motivation and in the number of indicators of digital readiness.

Micro Small Medium Enterprises (MSMEs) in Indonesia benefit from the digital era. It is important to apply digitalization in the Indonesian MSMEs so that they can develop and compete with other countries, and digital readiness is one of the key successes in the global competition.

We use the Duclos, Makdissi and Wodon (2005) decomposition of programme dominance into targeting dominance and allocation dominance curves to identify poverty-reducing programme reforms. In particular we recognise the importance of considering more than one dimension when identifying poverty-reducing policy reforms. For this purpose, we use sequential stochastic dominance methods to analyse the poverty impact of policy programme reforms, particularly the case of income transfers and commodity taxation.

We show that, even with flexible domestic wages, international outsourcing may worsen the welfare of the home country and reduce the profits of all firms. If wages are rigid, outsourcing is welfare-improving if and only if the sum of the “trade creation” effect and the “exploitation effect” exceeds the “trade diversion” effect. A wage subsidy may improve welfare. We also extend the model to a two-period framework. Delaying outsourcing can be gainful because the fixed cost of outsourcing may fall over time. A social planner would choose a different speed of outsourcing than that achieved under laissez-faire.

Lewbel and Pendakur (2009) developed the idea of implicit Marshallian demands. Implicit Marshallian demand systems allow the incorporation of both unobserved preference heterogeneity and complex Engel curves into consumer demand analysis, circumventing the standard problems associated with combining rationality with either unobserved heterogeneity or high rank in demand (or both). They also developed the exact affine Stone index (EASI) implicit Marshallian demand system wherein much of the demand system is linearised and thus relatively easy to implement and estimate. This chapter offers a less technical introduction to implicit Marshallian demands in general and to the EASI demand system in particular. I show how to implement the EASI demand system, paying special attention to tricks that allow the investigator to further simplify the problem without sacrificing too much in terms of model flexibility. STATA code to implement the simplified models is included throughout the text and in an appendix.