An HEI-Disaggregated Input-Output Table for Scotland

This paper describes how the education sector of the Scottish Input-Output tables is disaggregated to identify a separate sector for each of Scotland’s twenty Higher Education Institutions (HEIs). The process draws on accounting and survey data to accurately determine the incomes and expenditures of each institution. In particular we emphasise determining the HEIs incomes source of origin to inform their treatment, as endogenous or exogenous, in subsequent analyses. The HEI-disaggregated Input- Output table provides a useful descriptive snapshot of the Scottish economy and the role of HEIs within it for a particular year, 2006. The table can be used to derive multipliers and conduct various impact studies of each institution or the sector as a whole. The table is furthermore useful to calibrate other multi-sectoral, HEI disaggregated models of regional economies, including Social Accounting Matrix (SAM) and computable general equilibrium (CGE) models.

An HEI-Disaggregated Input-Output Table for Wales

This paper describes how the education sector of the Welsh Input-Output tables is disaggregated to identify a separate sector for each of Wales’s twelve Higher Education Institutions (HEIs). The process draws on accounting and survey data to accurately determine the incomes and expenditures of each institution. In particular we emphasise determining the HEIs incomes source of origin to inform their treatment, as endogenous or exogenous, in subsequent analyses. The HEI-disaggregated Input-Output table provides a useful descriptive snapshot of the Welsh economy and the role of HEIs within it for a particular year, 2006. The table can be used to derive multipliers and conduct various impact studies of each institution or the sector as a whole. The table is furthermore useful to calibrate other multi-sectoral, HEI-disaggregated models of regional economies, including Social Accounting Matrix (SAM) and computable general equilibrium (CGE) models.

An HEI-Disaggregated Input-Output Table for Northern-Ireland

This paper describes how the education sector of an Input-Output table for Northern Ireland is disaggregated to identify a separate sector for each of the four Northern Irish Higher Education Institutions (HEIs). The process draws on accounting and survey data to accurately determine the incomes and expenditures of each institution. In particular we emphasise determining the HEIs incomes source of origin to inform their treatment, as endogenous or exogenous, in subsequent analyses. The HEI-disaggregated Input-Output table provides a useful descriptive snapshot of the Northern Irish economy and the role of HEIs within it for a particular year, 2006. The table can be used to derive multipliers and conduct various impact studies of each institution or the sector as a whole. The table is furthermore useful to calibrate other multisectoral, HEI-disaggregated models of regional economies, including Social Accounting Matrix (SAM) and computable general equilibrium (CGE) models.

Disaggregating the Household Sector in a 2004 UK Input Output Table and Social Accounting Matrix by Income Quintiles

This paper disaggregates a UK Input-Output (IO) table for 2004 based on household income quintiles from published survey data. In addition to the Input-Output disaggregation, the household components of a UK Income Expenditure (I-E) account used to inform a Social Accounting Matrix (SAM),have also been disaggregated by household income quintile. The focus of this paper is on household expenditure on the UK energy sector.

Extending contingency: the impact of strategy, technology, size and business environment on the organisational form of small Chinese firms

This paper is inspired by articles in the last decade or so that have argued for more attention to theory, and to empirical analysis, within the well-known, and long-lasting, contingency framework for explaining the organisational form of the firm. Its contribution is to extend contingency analysis in three ways: (a) by empirically testing it, using explicit econometric modelling (rather than case study evidence) involving estimation by ordered probit analysis; (b) by extending its scope from large firms to SMEs; (c) by extending its applications from Western economic contexts, to an emerging economy context, using field work evidence from China. It calibrates organizational form in a new way, as an ordinal dependent variable, and also utilises new measures of familiar contingency factors from the literature (i.e. Environment, Strategy, Size and Technology) as the independent variables. An ordered probit model of contingency was constructed, and estimated by maximum likelihood, using a cross section of 83 private Chinese firms. The probit was found to be a good fit to the data, and displayed significant coefficients with plausible interpretations for key variables under all the four categories of contingency analysis, namely Environment, Strategy, Size and Technology. Thus we have generalised the contingency model, in terms of specification, interpretation and applications area.