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²² Even if there were many MPs with business interests that have not been identified, the argument still is strained, since the extent of unidentified holdings would have to be quite large in order for portfolio diversification by itself to be decisive.

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⁴⁴ An additional pecuniary interest relevant only to Tory MPs was their access, and that of their family and supporters, to government patronage. According to information provided by Pinto-Duschinsky, the amount of patronage controlled by the government in the mid-nineteenth century was still quite substantial; thus, the heavy support by office-holders for Peel's Corn Law legislation noted by Aydelotte could have had a pecuniary basis. A logit regression performed solely on Tory MPs with office-holding as a dichotomous dependent variable reveals that office-holders differed from their non-office-holding counterparts in their greater business holdings and in the tendency for their constituents to grow less corn and to riot less. See Pinto-Duschinsky, Michael, British Political Finance, 1830–1980 (Washington, DC: American Enterprise Institute for Public Policy Research, 1981), p. 18.Google Scholar

⁴⁵ This figure is based on 1866 data, which revealed that a little over 30 per cent of total acreage was planted in corn. Since productivity had improved, while output had declined, the obvious implication is that corn acreage was greater twenty years before. See Parliamentary Papers, 60 (1866), 6–9.Google Scholar

⁴⁶ For a recent, sophisticated example, see Gilligan, Thomas W., Marshal, William J. and Weingast, Barry R., ‘A Reconsideration of the Railroad Problem: The Economics and Politics of the Interstate Commerce Act’ (working paper, Domestic Studies Program, Hoover Institution, Stanford University, 1987).Google Scholar

⁴⁷ Olney, R. J., Lincolnshire Politics 1832–1885 (Oxford: Oxford University Press, 1973) describes a situation which is generally consistent with this.Google Scholar

⁴⁸ A third potential source of a relation between constituency characteristics and MPs' voting patterns is that an MP's portfolio of economic assets may have been geographically concentrated in the district which he represented; unfortunately, since the data on their economic assets merely tell us what type of assets they held without describing where the asset was located, we cannot evaluate the importance of this factor.

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⁵⁰ It should also be noted that t-statistics are only reported here for single divisions. Had the data for all divisions been pooled, or had we computed the joint significance of results for several equations, the strength of the reported statistical relationships between variables would appear to be stronger than it is in the single equation case. This is because the regression results across all divisions were broadly similar.

⁵¹ It is always possible that corn growers are the primary customers of some other producers, and so these producers' interest in repeal may be diluted or even reversed by their rational desire not to reduce the incomes of their customers. However, we have no data which would permit us to estimate the importance of such a relationship.

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⁵⁷ In addition, in an analysis not reproduced here, party variables are added to the right-hand side of the basic model of Corn Law voting to determine which variables remain significant when they are jointly used to account for floor votes. Although collinearity of course weakens the overall goodness-of-fit, in this context it is not overall goodness-of-fit that is of interest. Instead, the main objective is to identify which variables exhibit some independent effects when they are combined into a single regression.

⁵⁸ The regression results are also supplemented by an analysis of members' positions on a three-point Guttman scale derived from Aydelotte's Guttman scale of Corn Law voting. In general, the parameter estimates and goodness-of-fit measures did not vary dramatically across regressions.

⁵⁹ In a ‘spatial’ model voters choose a party or candidate in order to secure the adoption of policies which are the shortest ‘distance’ from their own ideal policies when these policies are mapped on to a space. The simplest useful spatial model is one in which the voter's location on a left-right continuum is compared with the location of various policy packages on the same continuum. An early but still useful example of this genre is found in Downs, Anthony, An Economic Theory of Democracy (New York: Harper, 1957).Google Scholar

⁶⁰ This technique is designed for situations where the left-hand side variable is restricted in the values it can make. In such a situation ordinary least squares estimation is inappropriate. For a helpful introductory discussion, see Aldrich, John H. and Nelson, Forrest D., Linear Probability, Logit and Probit Models, Sage University Paper Series on Quantitative Applications in the Social Sciences, 07–045 (Beverly Hills and London: Sage Publications, 1984).CrossRefGoogle Scholar

⁶¹ Belsey, David A., Kuh, Edwin and Welsch, Robert E., Regression Diagnostics: Identifying Influential Data and Sources of Collinearity (New York: John Wiley, 1980)CrossRefGoogle Scholar. Although some collinearity is present in the data, it is important to note that its effect is to decrease the efficiency of the parameter estimates, but not to bias them. Thus, when statistically significant relations are found in spite of collinearity, one can be reasonably certain that if one adopted some technique for removing the collinearity, the relationships would be even stronger, rather than disappearing.

⁶² This statistic is useful for measuring goodness-of-fit in situations where the model is non-linear. Large negative values indicate a large reduction in unexplained variance compared to a null model. For more information, consult Harvey, A. C., The Econometric Analysis of Time Series (Oxford: Philip Allen, 1981), pp. 159–65.Google Scholar

⁶³ This analysis was corroborated by regressions performed on two sub-populations: those MPs who did not return to Parliament in 1847, and those who did. The results showed that protectionists who dropped out or who were defeated for re-election tended to be more responsive to corn and sheep and less responsive to cotton and cattle than the ones who returned in 1847. This is exactly the pattern of results one would expect if constituency economic interests shaped the voting behaviour of Parliament by natural selection. It is interesting that the personal pecuniary variables also do not predict voting as well for the drop-outs as for those who returned.

⁶⁴ Re-analysis of the voting after excluding constituencies with less than 1,000 registered voters revealed no dramatic differences in the results.

⁶⁵ Aydelotte's dataset is so arranged that it is not possible to determine why a member was absent for a vote. If the reason were death, resignation or some other factor not plausibly connected to Corn Law voting in any systematic manner, such instances would of course reduce the efficiency of the estimates.

⁶⁶ Involvement in a business or the involvement of one's father in a business, representation of a county with rioting in 1842, less corn production than average, and not being a member of the landed class were more weakly associated with switching to a liberalizing position.

⁶⁷ The analysis of voting on the Corn Laws uses only a three-fold division of members into parties rather than the four-fold division adopted here. Dividing the Tories into Peelites and protectionists creates a situation where two of the twelve cells in a 4 × 3 matrix are empty: there are no Peelites in the hard-core protectionist camp and there are no protectionist Tories in the free-trade camp.

⁶⁸ A regression combining the party variables and the basic model was also run for both the vote on Villiers' motion and on Peel's bill. In the equations for protectionist voting the inclusion of party variables moved the coefficient on LAND to near zero and actually caused the coefficient on CORN to change sign. Other coefficients were not as dramatically affected. Since the coefficient on TORY was large and highly significant it is apparent that the strong relationship between membership in the Tory party and association with the landed class and corn-growing areas accounts for these results. The only important difference between the results for the two regressions is that protectionist voting on Villiers' motion displayed a strong negative relationship to representation of areas where rioting had occurred (coef = 0.880, t = 2.47).

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⁷² This is true even with regard to the Irish Repealers and the emerging potato famine, which seems to have had remarkably little effect on the content of the Repealers' political demands. See Woodham-Smith, Cecil B., The Great Hunger: Ireland 1845–1849 (New York: Harper & Row, 1962).Google Scholar

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