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UK public expenditure Patterns of change 1948-2002

UK public expenditure Patterns of change 1948-2002. Maurice Mullard and Allan Reese University of Hull. Theory of Public Expenditure 1. Explaining Public Expenditure growth Wilensky (1974) Castles (2001) : Expenditure and GDP: economic development relates to public expenditure

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UK public expenditure Patterns of change 1948-2002

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  1. UK public expenditurePatterns of change1948-2002 Maurice Mullard and Allan Reese University of Hull

  2. Theory of Public Expenditure 1 Explaining Public Expenditure growth • Wilensky (1974) Castles (2001) : Expenditure and GDP: economic development relates to public expenditure • Klein (1976) : Growth State idea private and public consumption • Contrast with Galbraith or Downs private affluence and public squalor

  3. Theory of Public Expenditure 2 Social Policy argument • expenditure demand-led • demography : longevity • number of children in schools Expenditure has its own momentum

  4. Politics - the 50s • Emergence from post-war austerity • Welfare state: cradle to grave security • Redevelopment of infrastructure • Defence: cold war and attempted world role • End of empire: wind of change

  5. Politics - the 60s and 70s • “Politics does not make a difference” Rose (1984) • Mapping out complex political events – idea of a Butskellite Consensus • Governments’ anti-inflation strategy; influence of trade unions; social contract • IMF visit of 1976 – break with Keynesian thinking

  6. Politics - the 80s and 90s • Escapable & inescapable expenditure– current versus capital components • State versus individual responsibilities • Mapping out … • the Thatcher years • the Major government • the Blair government

  7. Social security Education Health Housing Defence Law Roads Trade & industry Environment Agriculture Data series in this research

  8. Example series: Education (adjusted to billions of pounds @2000 )

  9. Personal Education Social security Health Housing Security Defence Law Infrastructure Roads Trade & industry Environment ( Agriculture ) Series grouped in Categories

  10. “Personal” expenditure total(billions of 2000 pounds)

  11. Programmes prone to change • Environment, Roads, Trade & Industry • Issues of subsidies • Shifts in industrial policy • Via’ing between categories of spending

  12. Character of programmes • Robust programmes difficult to change in the short term: education, health, social security • Relative soft programmes: housing • prior to 1974 used in anti inflation strategy • after 1974 no longer a political priority • Defence – the enabling programme

  13. The Research Question • public expenditure decisions represent an internal budget process • changes in education expenditure represent a relation to other expenditure programmes: zero sum argument • or decisions are externally decided • may depend on GDP for current or previous years • or decisions are politically driven • Politics does makes a difference:Labour and Conservative demonstrate different policy priorities

  14. Time-series Analysis • Data have internal correlations • Annual series covering 50 years • Already adjusted to “real terms” (at 2000) • Still show systematic gross changes • Fit trend line rather than take differences • Residuals from trends retain “local” autocorrelations - within period of office

  15. Social Security total - regression fits

  16. Social Security Residuals (from quadratic)

  17. Alternative analysis • Trends or year-on-year differences? • Differencing removes all autocorrelation • Local ACs may represent “policy” • Differenced ACs represent “laws of nature” • Education here shows classic autocorrelation of Box-Jenkins AR(1) model

  18. Next stage • No necessary periodicities • Can we detect business or political cycles? • De-trended series should be stationary • Look for cross-correlations • Do changes relate to GDP? • Look for internal structures - via’ing

  19. Displaying cross correlationseg, defence & education

  20. Correlations between series • Defence Health -@5 Environment -@3 Trade -@0 Housing -@5 • LawHealth +@7 Roads +@0 -@5 Trade +@1 Social +@1 • EducationHousing +@0 Social +@0 • Health Environment +@0 Housing +@0 • Env’ment Law -@5 Roads -@5 Trade +@1 Housing -@6 Social +@1/4 -@6 • Roads Defence -@3 Health +@6 Trade +@1 • Trade Law -@7 Education +@5/7 Health +@5/7 Roads -@5 Housing +@5 Social +@0 -@6/7 • Social Law -@5 Health +@7 Roads -@5

  21. Correlation needs investigationEducation & Health ( no lag )

  22. So what happens with GDP? GDP may lead (enabling factor): Education, Health, Housing May in turn be led by (stimulated growth): Environment, Roads But negative relationship with: Defence, Law NO simple relationships with Conservative/Labour as a dummy variable

  23. Explaining cross-correlations • Idea of clusters • Programmes that move in the same direction • winners and losers • Trade-offs • Politics does make a difference • In the way the government reacts to events?

  24. Social Security & Trade

  25. Health enabled by Defence

  26. Housing enabled by Defence

  27. Health - accelerating growth

  28. Health as percentage of GDP

  29. Rise and fall of Housing (TBA)

  30. Housing totalas percentage of GDP

  31. Housing transfers & capitalas percentage of GDP

  32. Environment current & capitalas percentage of GDP

  33. Trade transfers & currentas percentage of GDP

  34. Graphing three-way split • Three components that add up to 1 (or 100%) contain just two pieces of information • They can be plotted in 2-D on an equilateral triangle • Can look for clusters of points or a pattern of movement (locus) over time

  35. Triplot - division of spending

  36. What can we see in Education? • 1962-73 Capital up Subsidy up Current down • 1974-79 Capital fast down Subsidy up Current up • 1979-92 Capital down Current up • 1992-97 Capital up Current down • Since 1997 Current up

  37. Analysis + graphics Command-driven audit trail production line use Very versatile Extensible (like Unix) Widely used and with good user support Note irregular scales and axis labels Combinations of points and lines Graphs are built up by adding options to basic commands Good books + online documentation Comments on Stata

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