公共行政 外文文献 英文文献 05

Empirical Economics(1999)24:361±372
EMPIRICAL
ECONOMICS
(Springer-Verlag1999
Estimating the public's social preference function between in¯ation and unemployment using survey data: The survey research center versus Gallup*
David J.Smyth1,Pami Dua2,Susan W.Taylor3
1Middlesex University Business School,London NW4,United Kingdom
(e-mail:d.smyth@)
2Department of Economics,University of Connecticut,Stamford,Connecticut06903,USA
3Department of Economics,Millsaps College,Jackson,Mississippi39210,USA
(e-mail:taylosw@)
First version received:October1995/®nal version received:July1998
Abstract.Economists often use Gallup Poll data on presidential performance to analyze the interaction between politics and the state of the macroeconomy. The household survey undertaken by the Survey Research Center(SRC)of the University of Michigan provides an alternative data base.The SRC asks respondents about the government's performance speci®cally with respect to in¯ation and unemployment.We compare whether the Gallup or SRC data are the more useful for estimating the public's social preference function be-tween in¯ation and unemployment for the Carter,Reagan,Bush and Clinton presidencies.The estimates that use Gallup Poll data are unsatisfactory be-cause for two of the periods the coe½cients of in¯ation and unemployment are not well estimated and for one period there is serial correlation of the re-siduals.The estimates using the SRC data set are satisfactory and the results are consistent with economic theory.We conclude that a researcher using survey data to estimate the public's reaction to varying rates of in¯ation and unemployment should prefer the SRC series when it is available.
Key words:Estimating the Social Preference Function
JEL classi®cation:H00
I.Introduction
Economists and political scientists have long been interested in the reaction of the public to macroeconomic variables,especially in¯ation and unemploy-ment.A particular topic of interest is the shape of the public's social prefer-
*An earlier version of this paper was presented at seminars at Oakland and Michigan State Universities.We thank the seminar participants and two anonymous referees for comments.
362 D.J.Smyth et al. ence function between in¯ation and unemployment.Many studies investigate this function by estimating relationships between presidential popularity and variables measuring the state of the economy.1Most of these studies use monthly Gallup Poll data.Since January1978the Survey Research Center (SRC)of the University of Michigan has undertaken monthly surveys of households.Included in each survey is a question about the performance of the government with respect to the state of the economy,measured by in¯a-tion and unemployment.Several studies have used responses to this SRC question to calculate indices of satisfaction with the state of the economy and have related the indices to the behavior of in¯ation and unemployment.2In the present article we investigate whether the Gallup data or the Survey Re-search Center(SRC)data are the more useful for estimating the public's social preference function between in¯ation and unemployment.
II.The model
Theoretical analyses of macroeconomic policy commonly represent the pub-lic's social preferences between in¯ation and unemployment by an indi¨erence map that is concave to the origin.Most assume that the functional form is quadratic.We shall estimate such quadratic social preference functions.
We use the following variables:
Y a proxy measure for public satisfaction with the state of the economy which is evaluated in terms of the rates of in¯ation and unemploy-
ment;
YÃ the value of the proxy measure after the public's perceptions have fully adjusted to the in¯ation and unemployment rates;
P the in¯ation rate;
U the unemployment rate;
t month;
e disturbance term.
The quadratic social preference function is
YÃ o 1P2 2U2 1
The proxy variables are de®ned so that the larger is YÃ,the greater the level of satisfaction with the state of the economy.Accordingly,the coe½cients in the model have the following expected signs: 0b0Y 1 0Y 2 0.
We assume that the respondents to the Gallup and SRC surveys use the most recent information on in¯ation and unemployment that they have
1Examples are Mueller(1970),Kenski(1977)Kernell(1978),Monroe(1978),Monroe(1981), Michaels(1986),Frey and Schneider(1978),Golden and Poterba(1980),Kenski(1980),Shapiro and Conforto(1980a),Shapiro and Conforto(1980b),Maloney and Smirlock(1981),Chappell (1983),MacKuen(1983),Norpoth and Yantek(1983),Chappell and Keech(1985a),Chappell and Keech(1985b),Ostrom and Simon(1985),Richards(1988),Smyth,Washburn and Dua(1989), Smyth,Taylor and Dua(1991),Smyth and Taylor(1992a),Smyth and Taylor(1992b),Richards (1993),Dua,Smyth and Taylor(1995),Smyth,Dua and Taylor(1995).
2See Smyth and Dua(1988),Smyth and Dua(1989),Dua,Smyth and Taylor(1995).
Estimating the public's social preference function363 available.We estimate the model with monthly data so that this consists of the in¯ation and unemployment rates for the previous month and therefore
YÃt 0 1P2tÀ1 2U2tÀ1 2
We link Y t and YÃt by a partial adjustment process because people may only slowly become aware of the changes in the rates of in¯ation and unem-ployment and so may take some time to adjust their perceptions of the state of the economy.Adding an error term,we have
Y tÀY tÀ1 YÃtÀY tÀ1 e t 3
where0` 1.The public adjusts its perceptions about the economy to the long run or equilibrium level by a proportion in any month.The larger is , the faster the adjustment process.If 1,then adjustment is complete im-mediately.
Substituting for YÃt from(2)into(3)and rearranging yields the equation to be estimated
Y t 0 1P2tÀ1 2U2tÀ1 1À Y tÀ1 4 III.Data
Our®rst proxy measure of the extent of public satisfaction with the state of the economy uses Gallup Poll data.It is the percentage of respondents who answered``approve''to the Gallup Poll question:``Do you approve or disap-prove of the way Mr.is handling the job of President?''We call this measure GAL.We a monthly series for GAL using tabulations in Edwards(1990)and various issues of the Gallup Report.When there is more than one poll in any month we took the average of the polls during that month.
The second measure is based on responses to a monthly survey of approx-imately500households(a country-wide random sample)undertaken by the Survey Research Center of the University of Michigan.The SRC asks the question``As to the economic policy of the governmentÐI mean steps taken to®ght in¯ation or unemploymentÐwould you say that the government is doing a good job,only fair,or a poor job?''3From the summary of responses we calculated a monthly index of satisfaction with the government's perfor-mance with respect to the economy,SRC given by
SRC Good Fair Good a Good Poor 5
where``Good,''``Fair''and``Poor''are the percentages of respondents an-swering accordingly.The construction of SRC allocates the``Fair''responses to``Good''and``Poor''proportionately to the percentages responding ``Good''and``Poor.''If the number of respondents who rate the government's
3For information on the SRC survey see Curtin(1982).
364 D.J.Smyth et al. performance with respect to the economy as``Good''is equal to the number responding``Poor''then SRC 50.The more satis®ed households are with the state of the economy,the larger is SRC.The SRC started its monthly surveys in January1978.We calculated a monthly series for SRC using data provided by the Survey Research Center at the University of Michigan.
The in¯ation rate,P,is the percentage increase in prices over the past twelve months calculated from the consumer price index,all urban consumers, all items.The unemployment rate,U,is the percentage of unemployed civilian workers16years and older,seasonally adjusted.Both series were obtained from CITIBASE.
It is possible that the extent of the public's satisfaction with the state of the economy is a¨ected by non-economic variables and that such variables should be added to equation(3).One possibility is a honeymoon variable to re¯ect the public's realization that the economic conditions that persist during the ®rst months of an Administration are not attributable to the new president's economic policies.We specify a honeymoon variable as a dummy trend vari-able.It takes the value of10in March of the®rst year of the tenure of an Administration and declines by one each month to December of that year. Elsewhere its value is0.The coe½cient of the honeymoon variable is denoted by g.We expect g 0as the honeymoon e¨ect wears o¨over time.We found a signi®cant honeymoon variable for President Reagan.We tested for,and did not®nd,a honeymoon for Presidents Bush and Clinton and so do not include a honeymoon variable for their presidencies.There is no honeymoon period for the Carter presidency because estimation starts in1978,one year into Carter's term.4
A zero-one dummy variable can capture the negative e¨ect of the Iran-Contra a¨air on the Reagan presidency.We do not include such a dummy variable because,as explained in the next section,it is both appropriate and convenient to break our estimation periods simultaneously as the Iran-Contra a¨air became public.In December1989the US intervened in Panama causing a brief surge in President Bush's popularity.During the Gulf War,President Bush's popularity®rst fell because of growing uncertainty and then climbed and then fell again.It is not easy to model such bursts of public concern and euphoria and so the months of January and February1990and the period October1990to March1991are dropped from the analysis.
IV.Estimation procedures
It would be convenient if just one function could be®tted over the whole data set.In the model the constant term, 0,is the baseline measure of the public's rating of the president with Gallup Poll and of the Administration's macro-economic policy,with SRC survey,calculated where in¯ation and unemploy-
4We recognize that the use of a dummy variable that is truncated after ten months is rather arbitrary.At the suggestion of a referee we experimented with an inverse time trend which was allowed to approach zero over time.By using an inverse time trend we were able to test for a honeymoon e¨ect for the Carter years as well.We obtained insigni®cant results for the Carter, Bush and Clinton presidencies and the inverse trend was outperformed by the dummy variable for the Reagan presidency.
Estimating the public's social preference function365 ment are zero and all dummy variables are zero.Some presidents have greater underlying popularity than others so we expect 0to di¨er between presiden-tial regimes.Several researchers have allowed for this.However,using Gallup Poll data,Smyth,Dua and Taylor(1991,1995)found structural changes in the other coe½cients between presidential regimes.One way to allow for the possibility of such changes is to estimate separate regressions for di¨erent presidencies.Another strategy is to estimate the model over the whole time period incorporating regime dummy variables to capture discrete shifts in the parameters from regime to regime.5A disadvantage of both these procedures is that changes in the public's perceptions of the importance of in¯ation and unemployment may not coincide with changes in presidential terms.It seems wiser to allow the coe½cients to change as the economic environment changes rather than when the presidency changes hands.6Accordingly we have esti-mated the model for three separate periods.The®rst is the Carter presidency. The second is for the®rst Reagan term and the®rst half of his second term. The third is for the remainder of Reagan's second term together with the Bush and Clinton presidencies.We chose these periods using information on the behavior of in¯ation and unemployment and on the public's absolute and relative concern about the importance of in¯ation and unemployment as a national problem.
Our decision criteria can be explained the behavior of in¯ation and unemployment rates and responses to another Gallup Survey question.On an intermittent basis,the Gallup Poll asks the question``What do you think is the most serious problem facing the nation today?''The answers have ranged widely,but usually concerns with in¯ation or unemployment or both predominate.
During the Carter presidency in¯ation was high and unemployment low
5The following procedure can be used.De®ne dummy variables for each presidency,the Carter,®rst Reagan,second Reagan,Bush and Clinton presidencies.The dummy variable for any presi-dency takes the value one during that presidency and zero otherwise.All observations are multi-plied by these®ve dummy variable series.Estimation of the model then yields the coe½cients for each regime together with standard errors and t-statistics.The procedure generates one set of as-sociated statistics±the values of R2,the loglikelihood coe½cient and the LM(1)coe½cient for serial correction±for the whole time period.We followed this procedure in an earlier version of the paper,except that the analysis did not include the Clinton presidency.The two procedures are not entirely equivalent.The same regression coe½cients are obtained.However,due to di¨erences in the generation of error variance,the standard errors and t-statistics generated by the two pro-cedures are slightly di¨erent.
6Our procedure goes at least some way to meeting the Lucas critique which may apply.Recent work is not very supportive of the Lucas critique.For example,Ericsson and Irons(1995,p.301) show that``the Lucas critique is a possibility theorem,not an existence theorem.An extensive search of the literature reveals virtually no evidence demonstrating the empirical applicability of the Lucas critique.That search clari®es what sort of evidence would constitute support for the Lucas critique:much of the evidence cited in the literature is uninformed because it could arise from more mundane sorts of model misspeci®cation....An additional literature search®nds considerable evidence refuting the Lucas critique for speci®c macroeconomic equations across a number of countries.In addition,there is evidence that the public is backward looking rather than forward looking.Smyth,Dua and Taylor(1994)compared the hypothesis that presidential popularity depends on recently observed in¯ation and unemployment to three alternative models that assume varying forms of forward looking behavior.Non-nested hypothesis tests rejected the forward looking models in favor of the one with the recent actual variables.
366 D.J.Smyth et al. until the last few months.The responses to the Gallup question re¯ect this. During the Carter presidency,approximately three times the number of peo-ple saw in¯ation as the most serious problem than saw unemployment as the most serious problem.Thus we expect that Carter's performance will be judged mainly on his anti-in¯ation e¨orts,not on anti-unemployment e¨orts. Accordingly,our®rst set of estimates is for the Carter presidency.
By the start of the Reagan presidency in¯ation was falling and unemploy-ment rising because of anti-in¯ation policies.As in¯ation fell the unemploy-ment rate declined.The public's concern about in¯ation declined from high levels at the beginning of Reagan's®rst term to low levels at the end of his second term.The public's concern about unemployment rose as the unem-ployment rate rose and then followed the unemployment rate down.Thus much of the Reagan presidency was a time of varying concerns about in¯ation and unemployment and so we expect both in¯ation and unemployment to be important during this period.By the fall of1986in¯ation is low and only a small percentage of people still view it as the country's major problem.Un-employment and the public's concern about it are still falling but many people still view it as the nation's most serious problem.This suggests another break point late in1986.Accordingly,our second set of estimates is for the period March1981to October1986.An advantage of choosing October1986as the ending date is that it means that we do not have to insert a dummy variable for the Iran-Contra a¨air that became public in November1986.The Iran-Contra a¨air caused a big decline in President Reagan's popularity.
For the rest of the Reagan presidency,and during the Bush and Clinton presidencies,unemployment is viewed as a more important problem than in-¯ation.We make our third set of estimates for the period January1987to December1995with breaks for the change of presidents,the Panama invasion and the Gulf War.Although the period from the beginning of1987onwards spans three di¨erent presidents,the major economic concern is the same.It is with unemployment.Because the three presidents may have di¨erent under-lying popularities we put in a separate constant for each president.
Our model is nonlinear.The nonlinearity does not arise because we have the squares of in¯ation and unemployment as independent variables.It occurs because of our partial adjustment speci®cation.For example,the coe½cient of P2tÀ1is 1which is a combination of two coe½cients.We make direct non-linear least squares estimates of the parameters in equation(6).This allows us to retrieve standard errors and t-statistics directly.7The estimates are made in
7We can rewrite the model so that it is linear in the parameters as follows
Y t x0 x1P2tÀ1 x2U2tÀ1 x3Y tÀ1 e1
where x0 0,x1 1,x2 2and x3 1À and estimate it by ordinary least squares.The disadvantage of this procedure is that the estimated x coe½cients are short-run response co-e½cients.We are interested in the long-run or equilibrium coe½cients,the coe½cients,and the speed of adjustment, .The equilibrium values can be retrieved and calculated.For example,as 1Àx3,it follows that 1 x1a x1a 1Àx3 .However,this process yields only point esti-mates of the parameters and it is necessary to estimate the standard errors of the coe½cients indirectly.
Estimating the public's social preference function367 EVIEWS using the iterative Marquardt technique to®nd the minimum of the sum of squares.8
The availability of SRC data constrains the starting point of our analysis, February1978,one year into the Carter presidency.Monthly SRC data are not available until January1978and we lose that month to the lagged de-pendent variable.For the Reagan,Bush and Clinton presidencies the®rst usable observation is for March of the®rst year of the presidential regime.A new president takes over in January and the®rst full month that he is presi-dent is February.Since our partial adjustment model requires that we have the president's popularity in the previous month,the earliest month that we can use in our analysis is March of his®rst term.We end with October of the last year of a presidency as this is the last month before the presidential election. It is possible that rating may be distorted after the election.9The last obser-vation for the Clinton presidency at the time of writing is December1995.
We need to set up criteria for choosing the best data set,Gallup or the Survey Research Center.We use two criteria,one based on serial correlation of the residuals and the other on the sign and signi®cance of the estimated values of 1and 2,the in¯ation and unemployment coe½cients.First,if a data set for any presidential term yields serially correlated residuals we view that as a symptom of speci®cation error and conclude that the data set is un-satisfactory.We use the LM(1)test statistic as our measure of serial of corre-lation of residuals.10The second criteria comes into play if one or both data sets pass the serial correlation test.Suppose both data sets show no sign of serial correlation.We then prefer the data set with both 1and 2coe½cients correctly signed and signi®cant at the.05probability level over the data set with one or zero signi®cant and correctly signed coe½cients.Similarly we
8EVIEWS(1995,P.203)describes the procedures as follows.``Non linear estimation uses the Marquardt algorithm in the following way.At each iteration,it computes approximate derivatives with respect to each parameter,by making a small change in the parameters,one at a time,and seeing how much the equation changes as a result.It then regresses the dependent variable on the derivatives.When necessary it uses ridge regression in order to avoid problems of collinearity,but the®nal results do not involve ridge regression.The regression gives a vector of proposed changes in the parameters.Eviews then evaluates whether the proposed changes actually decrease the sum of squared residuals.If they do,it adopts the changes and starts a new iteration.If not,it tries a fraction of the changes.In principle,there should be some fraction which that improvement is obtained.This process is continued until the proposed changes are very small compared to the parameters themselves.''
9For example,in December1988,President Reagan's last full month in o½ce,his approval rat-ing measured by GAL rose to63percent from57percent in November,without any marked change in the state of the economy.This sharp increase may have re¯ected a benevolent farewell to the departing president.
10LM(1)is the Lagrange multiplier test statistic for®rst order serial correlation distributed asymptotically as w21with critical value3.84at the0.05probability level.If there is signi®cant autocorrelation of the residuals we do not reestimate the equation with a correction for residual autocorrelation.While such a procedure is common it is inadvisable.Mizon(1995,p.267and p.285)``shows that even when a linear regression model has®rst order autoregressive errors,it is possible for autoregressive least square estimation(e.g.,Cochrane-Orcutt)to yield inconsistent estimates....Although it is important to test for serial correlation in the residuals of econometric models,it is rarely appropriate to`autocorrelation correct'in response to rejecting the hypothesis of zero serial correlation....Re-estimating a linear regression model by ALS imposes common factor restrictions,and inconsistent parameter estimates will result when the common factor re-strictions are invalid....The common factor restrictions imply very stringent constraints on the temporal structure of the variables being modelled,and as such are unlikely to hold in general.''
prefer the data set with one negative and signi®cant coe½cient over one with no negative and signi®cant coe½cient.If both yield the same number of ac-ceptable coe½cients we accept both as satisfactory and cannot choose between them.If neither have negative and signi®cant coe½cients,we regard both as unsatisfactory.As we have de®nite expectations on the signs of the coe½-cients we use one-tailed tests of signi®cance for the t -statistics throughout.V.Results
The results for the three estimation periods are given in Tables 1,2and 3.In each table we show results for the two dependent variables,GAL and SRC.We report the estimated coe½cients,their t -statistics,the adjusted R 2and the Lagrange multiplier LM(1)test statistic for serial correlation.
Table 1reports the results for the Carter presidency.The Gallup estimates,in column (1),fail on both counts.The residuals are serially correlated ±the LM(1)coe½cient is 6.19which is signi®cant at the .05level.Both the in¯ation and unemployment coe½cients are quite insigni®cant.In contrast,for the SRC estimates in column (2),the LM(1)coe½cient is a negligible 0.69.The in¯ation coe½cient is signi®cant at the .01level.The unemployment coe½-cient is insigni®cant.Column 3reports the results for the SRC measure when the unemployment variable is dropped.Again there is no serial correlation and the in¯ation coe½cient remains highly signi®cant.
The results for the period March 1981to October 1986are shown in Table 2.Both the Gallup Poll and Survey Research Center results are satisfactory.There is no evidence of serial correlation and in both the regressions the 1and 2coe½cients are easily signi®cant at the .01probability level.
Table 3gives the estimates for the remainder of the Reagan presidency and the Bush and Clinton presidencies.Again there is no evidence of serial corre-lation with either data set.The Gallup data results are reported in column (1).
Table 1.Estimated social preference functions 1978.03to 1980.10(t -statistics in parentheses)
368
D.J.Smyth et al.
Estimating the public's social preference function369 Table2.Estimated social preference functions1981.03to
1986.10(t-statistics in parentheses)
Table3.Estimated social preference functions1987.01to1988.12,1989.03to
1989.12,1990.03to1990.09,1991.04to1992.10and1993.03to1995.12
(t-statistics in parentheses)
370 D.J.Smyth et al. The coe½cient of unemployment is negative and signi®cant at the.05level. However the coe½cient of in¯ation has the wrong sign,it is positive and it is signi®cant at the.01level.With the SRC data in column(2)there is no evi-dence of serial correlation and the unemployment coe½cient is negative and easily signi®cant at the.01level.In¯ation is not signi®cant.When in¯ation is dropped in column(3)there is still no serial correlation at the.05level and the unemployment variable remains highly signi®cant.
For each of the three estimation periods the SRC estimates pass our crite-ria as in each period at least one of the in¯ation and unemployment variables is negative and signi®cant and the residuals are not serially correlated.With the SRC data set we®nd that when in¯ation is high and the public regard in¯ation as an important problem the in¯ation coe½cient is negative and signi®cant.When unemployment is high and the public regard unemploy-ment as an important problem,the unemployment coe½cient is negative and signi®cant.
Only during one of the three periods are the Gallup results satisfactory. During the®rst period the residuals are autocorrelated and neither in¯ation nor unemployment is signi®cant.In the third period again neither in¯ation nor unemployment have a signi®cant negative coe½cient.Only during the®rst three years of the Reagan presidency does the Gallup data yield results con-sistent with our expectations.
VI.Conclusions
The research presented in this paper is not a test of model speci®cation but rather a test of data appropriateness.The estimates of the social preference function using the Survey Research Center data are much more satisfactory than those using the Gallup series.Thus we conclude that a researcher esti-mating the public's response to varying rates of in¯ation and unemployment should choose to use the SRC data rather than the Gallup data.
We believe that the evidence shows this because the SRC survey of opinion about the government's economic policy focuses on the economy while the Gallup survey is a more general one.The Gallup survey has been widely used because it is available over a long period±a consistent and usable Gallup se-ries can be constructed monthly(with a few gaps)back at least as far as the start of the Eisenhower presidency.Monthly SRC data are available only since January1978;earlier data for the mid month of each quarter are avail-able back to May1971.
While our econometric analysis causes us to express a preference for the SRC data,we do not want to overstate our conclusions.We have concentrated on one model,albeit one popular with economists.For other purposes or models,the Gallup series may be as appropriate,or even more appropriate, than the SRC series.Perhaps risk adverse researchers should undertake their analyses using both data sets.
Data appendix
GAL:Gallup Poll presidential approval data gleaned from various issues of Gallup Report。