defense contracting and domestic politics

University of Utah

Defense Contracting and Domestic PoliticsAuthor(s): Karl Derouen, Jr. and Uk HeoSource: Political Research Quarterly, Vol. 53, No. 4 (Dec., 2000), pp. 753-769Published by: Sage Publications, Inc. on behalf of the University of UtahStable URL: http://www.jstor.org/stable/449259 .

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Defense Contracting and Domestic Politics

KARL DEROUEN, JR., SOUTHWEST TEXAS STATE UNIVERSITY UK HEO, UNIVERSITY OF WISCONSIN-MILWAUKEE

Scholars have investigated the relationship between defense spending and domestic political constraints. Because of a two-year time lag, however, it is difficult to make a theoretical link between the aggregate defense budget and domestic politics. We focus on defense contract awards because of their rapid turn-around. We advance the referendum model to account for variations in the timing of defense contracts within administrations. The referendum model posits that government policies are reflective of approval ratings and that the President uses defense contracts to counter sagging approval and/or a weak economy. This is a subtle but important alternative to political business cycle (PBC) models which constrain political manipulation of the defense budget to the electoral cycle. An empirical model is tested using pooled time-series analysis which allows us to assess variation within administrations. The analysis reveals that presidential approval, war, presidential reelection, and unemployment are determinants of defense contracting.

It was a smart P R. man who changed the name of the War Department to the Defense Department--ever since then everything's gone up in Congress in a hoot and a holler.

-George McGovern in a 1991 interview

In an analysis done at the height of the Cold War, Hitch and McKean (1960: 66-67) urged that the indirect effects of defense spending not be abused. They recommended that

... the potential effects on stability should not dictate over defense policies. The scale and nature of defense expenditures should be decided on the basis of their

NOTE: We are appreciative of the comments, assistance and suggestions of David Garnham, Tom Holbrook, Joel Paddock, Anne DeRouen Jasien, Ray Morris, Barry Beckman and Ben Ford- ham. An earlier version of this article was presented at the Annual Meeting of the American Political Science Association, September 3-6, 1998, Boston, MA.

Political Research Quarterly, Vol. 53, No. 4 (December 2000): pp. 753-769

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Political Research Quarterly

merits as national security measures-and should not be regarded as counter- cyclical tools. This is not to say that the implications of the defense budget for stability can be ignored. They should be certainly recognized. But they should be dealt with chiefly by adjusting monetary-fiscal policies rather than by capri- ciously changing defense programs.

Many subsequent studies of the post-war U.S. defense budget have revealed that the warning of Hitch and McKean has not been heeded. According to a group of scholars (Griffin, Wallace, and Devine 1982; Mayer 1991, 1992, 1995; Mintz 1988; and Tufte 1978 for instance), Presidents have often manipulated defense budget to decrease unemployment just before an election. The reason for using the defense budget is that the major means of macroeconomic control are not accessible to the President (Rosati 1999: 82; see also Beck 1987). The Federal Reserve Board controls interest rates and the money supply. Taxation and government spending powers are vested within Congress. Moreover, most government spending is indexed and removed from presidential influence (Mayer 1991: 182). In other words, the President is severely curtailed in his ability to "fulfill the [economic] expectations" built up during the campaign (Rosati 1999). Thus, many argue that manipulating the defense budget is a good fiscal means by which an administration can boost the economy for political purposes (Mayer 1991; Russett 1990a).

The early cohort of studies linking defense spending, the economy, and politics were largely from the neo-Marxist school (e.g., Baran and Sweezy 1966; Boddy and Crotty 1975; Cypher 1974; Reich 1972; and Smith 1977). These studies generally claimed that the postwar U.S. economy was stabilized on the back of defense spending. Many argued that government would manipulate defense spending to protect corporate interests and/or to boost the economy for political gain. Griffin, Devine, and Wallace (1982) went further and showed that defense spending and procurement outlays were used to protect monopoly capital and increase the chances of reelection by reducing unemployment and stim- ulating investment.

The "second wave" has looked at the macroeconomic implications of defense spending from more of a liberal perspective (e.g., Cusack 1992; Mayer 1991, 1992, 1995; Mintz 1988; Mintz and Hicks 1984; Mintz, Huang, and Heo 1992; Mintz and Ward 1991; Nincic and Cusack 1979; Russett 1990b; Russett and Barzilai 1992; and Zuk and Woodbury 1986). While Zuk and Woodbury (1986) found no evidence of a postwar defense spending-electoral cycle nexus, most others did.

The seminal study of Nincic and Cusack (1979) melded the earlier radical works and the political business cycle (PBC) literature. They found that military expenditures stimulated the economy--conceivably in anticipation of elections-and compensated for shortfalls in private consumption and investment. Mintz (1988) demonstrated a connection between electoral cycles and military

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expenditures. Mintz and Hicks (1984) argued that as unemployment increased, defense spending followed to replace the lost jobs before elections. Similarly, Mintz, Huang, and Heo (1992) found that policymakers used military procurement to respond to poor economic conditions such as rising unemployment. Russett and Barzilai (1992) asserted that elected politicians can synchronize defense spending with elections in order to maintain high levels of public support and therefore remain in power. Cusack (1992) showed that U.S. defense spending was governed by domestic processes such as the electoral cycle and unemployment. Arguing that it provided a more accurate assessment of the political nature of defense spending, Mayer (1991) used defense prime contract awards (PCA) to correlate defense spending with electoral cycles.

While these studies have rigorously explored the connections between defense spending, the economy, and public opinion, there has been little empirical research on how the President might actually use the defense budget to counter weak approval during his term in office. Several scholars have shown there is a cycle of presidential approval (e.g., Brace and Hinckley 1992; Mueller 1970). The presidential term begins with relatively high poll numbers reflective of public anticipation. There is a brief honeymoon period. Soon thereafter, economic woes or other unanticipated events elicit a drop in approval. The decline in approval will concern the President because of its impact on his ability to provide leadership and win legislative support in Congress.

For these reasons, it may be that Presidents--victims of continuous polling, intense media scrutiny, and a general decline in approval--are likely to manipulate the defense budget in order to boost approval throughout their term rather than just at election time. Mayer (1991: 186), for example, stated that "[p]residents could also increase defense spending as a way of helping to bring the economy out of recessions, which are never good for presidential popularity." Griffin, Devine, and Wallace (1982: 147) similarly posited that leaders boost their popularity by using defense spending to increase investment and reduce unemployment.

If we are to test for the presence of a political component to the defense budget, we need to employ an appropriate measure of the phenomenon. The PCA is "a legally binding promise by the government to pay the contractor for specified goods and services" (Mayer 1992: 186). The administration has broad discretion in the timing of the PCA. There are several strong and theoretically compelling reasons for focusing on PCA with respect to manipulation of economic policy for political gain. First, defense procurement is an important component of the U.S. economy (Gansler 1995). While PCA may not have a tremen- dous macroeconomic impact, as Barro (1991) noted defense contract awards quickly generate jobs and increase purchasing power. Once contracts are awarded, jobs are created almost overnight as "contractors hire ... engineering, manufacturing, and management personnel, issue subcontracts, and gear up pro- duction facilities" (Mayer 1992: 186). Griffin, Wallace, and Devine (1982: 3)

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posited that the nature of weapons procurement makes contract awards a relevant topic. They wrote that "armaments are quickly consumed or become obso- lete, ensuring a never-ceasing demand for weapons."

Second, as Mayer (1991) pointed out, macroeconomic manipulation of the economy via the defense budget for political gain must be "quick" and "predictable." Since 1954 there has been a consistent pattern in which defense contracts go up by billions in the quarter just prior to federal elections (Mayer 1992: 16). Standard aggregate defense spending decisions, on the other hand, are made years in advance. The Executive Branch makes an annual defense budget request to Congress via the Department of Defense (DoD) and the Office of Management and Budget. Congress then appropriates the money. According to Berner and Daggett (1993), the entire process from DoD drawing board to actual outlays take about 26 months. DoD also prepares a Future Years Defense Plan which looks six years ahead. Furthermore, Con- gress typically amends the presidential defense budget requests.

Another important reason that aggregate defense spending is not a particularly useful political tool for the President is that defense spending has been shown to be sensitive to public opinion. For example, Hartley and Russett (1992) showed that public disapproval of defense spending had a negative impact on defense spending (see also Higgs and Kilduff 1993). Wlezien (1996) found that the public responds rather quickly to defense appropriations decisions. Furthermore, Congress more or less responds directly to public preferences for defense spending and adjusts its appropriations accordingly. In turn, public support reacts to the levels of appropriations. Thus there is evidence of policy-preference feedback that conceivably precludes the political abuse of aggregate defense spending.

In short, it becomes more difficult to make a case for aggregate defense spending as a tool for political manipulation of the economy. Using defense PCA circumvents these problems. PCA can be timed easily by Presidents. They can also be targeted to specific states where the economy might need shoring-up or the President's approval is sagging. The awarding of defense contracts, unlike aggregate defense spending levels, does not require congressional approval. The awarding of defense contracts involves monies already appropriated so public opinion is much less of an intrusive factor.

THE ECONOMIC MANIPULATION OF THE DEFENSE BUDGET FOR POLITICAL GAIN

As mentioned, many scholars assign domestic explanations to variations in the defense budget.' Below we trace the origins of two counter-cyclical models. The first captures the political business cycle (PBC)-i.e., the effect of the economy

1 Others have stressed the relevance of international tension and Soviet spending levels (e.g., Hart- ley and Russett 1992; Ostrom and Marra 1986; Zuk and Woodbury 1986).

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on electoral outcomes. The second focuses on the so-called perpetual election and the effect of the economy on public approval.

General Stimulation of the Economy and Electoral Cycles-the PBC Model

PBC theory asserts that voters retrospectively cast votes based more on past performance rather than promises of future benefits (Alt and Chrystal 1983: 158- 59). When chances of reelection appear threatened, a government could conceivably manipulate economic policy by utilizing incumbent advantages. Alt and Chrystal (1983: 104) outlined three central tenets of PBC theory: (1) governments desire to win elections and to do so, they attempt to maximize votes; (2) among economic outcomes, voters have preferences that are reflected in their voting behavior; and (3) governments can manipulate economies for electoral gain. PBC theory generally predicts economic prosperity in the second half of the President's first term, and slumps in the two years after the election (Haynes and Stone 1988; Nordhaus 1975).

Nordhaus (1975) assumed that the administration can set unemployment at whatever level it sees fit. From this, he turned to individual voter preferences and assumed that individuals use inflation and unemployment in their vote calculus rather than campaign platforms. Nordhaus stressed that since voters are extremely myopic, it would be to the incumbent's benefit to reduce unemployment as near to election time as possible.

Tufte (1978) presented evidence of two-year cycles in income, and four-year cycles in unemployment coinciding with presidential elections. Tufte showed that when an incumbent President is in a race, disposable income increases by over 3 percent, while in odd years it only increases by 1.5 percent. Tufte found that this translated into an increase in the vote for the incumbent by 2.4 percent. The even-year prosperity also increases the votes for the President's party in the house. Similarly, Fair (1978) found that the best predictors of the vote for the incumbent were from the growth rate of the GNP in the year of the election and the change in unemployment for the year of the election. Haynes and Stone (1988) reiterated that voters are myopic and retrospective, therefore the incumbent who lowers unemployment just before the election will reap dividends. Haynes and Stone discovered that unemployment bottoms out in the third quarter of presidential election years.

The Impact of the Economy on Presidential Approval-The Referendum Model

The referendum model posits that government policies are reflective of the government's approval rating (Frey and Schneider 1978; Rose 1991) throughout the administration. For example, the government monitors approval ratings in order to ascertain how the economy is affecting its popularity (Williams 1990). The perpetual election brought on by popularity polls and the media conditions Presidents to

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pay close attention to their standing in the polls. It is reasonable to expect that the President would be willing to tweak the economy in order to heighten his public image, and subsequently his stature in Congress at any point during his tenure. It is crucial to the President's influence in Congress that his public approval be fairly high if he is to have a chance to pass key legislation (Ostrom and Simon 1985; Rivers and Rose 1985; Stoll 1987). Furthermore, a President with very low approval, roughly below about 40 percent, has a reduced set of foreign policy options in times of crisis, for it is at this time when opposition is at its boldest (Ostrom and Job 1986). If the economy, and subsequently approval ratings, fall too low, no amount of manipulation may be able to remedy the situation at election time. Finally, fine-tuning the economy is important because, as mentioned, approval gradually declines over the course of an administration.2

In sum, the main argument of the referendum model is that Presidents "manipulate policy in the short run in reaction to innovations ... in approval rating" (Williams 1990: 788). According to Rose (1991), the President is perpet- ually seeking to maintain a high level of support throughout his tenure for con- tinued support from Congress and the public because declines in presidential approval comes with a concomitant decrease in the success rate of presidential policy initiatives. Similarly, Ostrom and Simon (1985: 686) argue that presidential approval, to a large extent, determines policy actions. Kernell (1997: 2) refers to the strategy "whereby a President promotes himself and his policies in Wash- ington by appealing to the American public for support as going public."

In terms of policy actions, Presidents may respond to negative approval by opting for policies which can create jobs and boost the economy such as by strategically timing the contract awards (see MacKuen 1983; Mayer 1991; Norpoth and Yantek 1983; Ostrom and Simon 1985). Since theoretical discussions generally agree that economic performance is a primary determinant of public support, the President is likely to proactively maintain his approval rating by making innovative economic policy decisions.

As we discussed, PCA are readily manipulable for political purposes and do not draw too much attention from the public. According to Mintz, Huang, and Heo (1992), there is no evidence of a direct relationship between inflation and military procurement (see also Starr et al. 1984). Thus, without generating noticeable side effects, PCA can be easily used as a tool to boost economic performance, such as reducing unemployment, which in turn improves presidential approval (see Fordham 1998a: 568).

For these reasons it is theoretically plausible to model presidential approval as a determinant of PCA. We will now specify a model capable of measuring the effects of domestic economic and political factors within administrations.

2 See Quandt (1988) for a treatment of the cyclical nature of presidential terms.

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RESEARCH DESIGN

The Dependent Variable: PCA

We contend that PCA is a relevant focus for analyses of the U.S. defense budget. PCA provide a President with a means of improving political fortunes by distributing benefits with great precision. Griffin, Wallace, and Devine (1982: 2) argued that the political implications of the defense budget spending are best studied over time. We contend that this also holds true for analyzing the PCA component of the defense budget, and to this end include a longitudinal aspect in the research design. Since we also want to assess the effect of several variables within administrations, we utilize a pooled analysis described below.

Independent Variables3

Approval. As discussed, Presidents are capable of manipulating government resources for political purposes. As the referendum model posits, maintaining a certain level of approval gives leverage to the President with respect to passing bills in Congress, exercising leadership, and succeeding in presidential policy initiatives (see Rose 1991). Thus, Presidents are likely to respond to the decline of presidential job approval ratings. We hypothesize that PCA will increase as approval declines.

Unemployment. According to Barro (1991), defense spending has a positive effect on economic output by generating jobs and increasing purchasing power of workers through contract awards. Mintz and Hicks (1984) showed that defense spending increases as unemployment rises. In a later study, Mintz, Huang and Heo (1992) also reported that military procurement increases as unemployment goes up (see also Griffin, Wallace, and Devine 1982). Because unemployment figures are reported on a monthly basis, it is reasonable to assume presidents could react to unemployment problems in a given quarter. For this reason we use current rather than lagged unemployment (see DeRouen 2000; Fordham 1998a).

War Involvement. It is logical to expect the increase of defense spending (including PCA) when a nation is involved in a war. Nincic and Cusack (1979) and Looney and Mehay (1990) demonstrated that the Korean and Vietnamese conflicts were important determinants of defense spending. Fordham (1998b)

3 We recognize that most of the literature from which we derive our variables refers to aggregate defense spending rather than PCA. However, there is little literature that deals specifically with the latter. We contend that there is significant correlation between the motives for PCA and defense spending. The real difference exists in the ability of the chief executive to time the awards. Or as Griffin, Wallace, and Devine (1982: 8) state, "domestic and economic influences on [aggregate defense spending] can broadly be generalized to the components of total defense spending [such as] procurement outlays."

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also recommends including the Persian Gulf War in postwar analyses because of the size of the troop deployment. Mayer (1991) also showed that defense contracts increased as the country mobilized for war. For these reasons we control for war involvement.

Electoral Cycles. Mayer (1991, 1992, 1995) showed the correlation between PCA and electoral cycles. Mayer (1991; see also Baldwin 1967; Gansler 1995) also argued that the primary economic benefit of PCA is jobs. The public tends to have the perception of economic performance based on the unemployment rate. Since the public perception of the economy is critical in elections and job approval, Presidents are concerned about unemployment particularly when the election is near (see Ostrom and Simon 1985). A group of scholars (Hibbs 1987; Mintz 1988; Tufte 1978) found evidence that Presidents have attempted to improve economic performance and reduce unemployment immediately prior to their reelections. Thus we hypothesize that electoral cycles, particularly presidential reelection, lead to PCA increases.

The Reagan Administration. Reagan entered office with a clear goal of rein- vesting in the military-industrial complex and used an increasingly large share of the defense budget for procurement (Mintz 1992; see also Farrell 1997). Mayer (1991) showed empirically that this Reagan boost in PCA was highly significant. For this reason we control for the Reagan years with a dummy variable.

The Empirical Model

Based on the above hypotheses and reasoning, we specify our empirical test as follows.

(Model I)

PCAit = ot + 1 APPROVALit + P2 UNEMPLOYMENTit + 33 WARit + 34 REELECTIONit + 35 REAGANit + eit

We also test this model with two other versions of the electoral cycle variable: all presidential elections (Model II) and national elections (Model III).1

Data

The observations are quarters from 1953 to 1992 (N = 160). PCA data are from the Department of Commerce's Survey of Current Business (1996). They were

4 We also tested the models using an additional international level control variable. We created a variable that looked at Soviet/Russian crisis behavior using Brecher and Wilkenfeld's (1997) Interna- tional Crisis Behavior data. This additional variable was not significant and did not change the signs and magnitude of the other variables in the models. The results are available from the authors upon request.

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converted to 1987 constant values using the implicit price deflator for GNP (1987 = 100) from the Bureau of Economic Analysis' National Income and Prod- uct Account of the United States. The deflator was updated through 1992 using the Survey of Current Business.

Presidential approval (APPROVAL) data are from Fordham (1998a) and are based on quarterly averages from Gallup polls. UNEMPLOYMENT data are from the Bureau of Economic Analysis' Survey of Current Business. The election variables are based on presidential reelection years in the case of PRESIDENTIAL REELECTIONS, all presidential election years in the case of ALL PRESIDENTIAL ELECTIONS, and even years from 1954 to 1992 in the case of ALL NATIONAL ELECTIONS. Our sense is that the most realistic time to expect manipulation of the economy for electoral gain is during presidential reelection years (DeRouen 1995; Fordham 1998a; Zuk and Woodbury 1986). The electoral cycles variables are coded as 1 in the four quarters of the relevant election year, and 0 otherwise. Data on WAR are based on the information in Spanier and Hook (1995). The quarters during the Korean, Vietnam, and the Gulf Wars are coded 1 and the others as 0. As mentioned, we controlled for the REAGAN administration by coding those quarters as 1 and 0 otherwise.

METHODS

Before turning to the results of our empirical analysis, there are three methodological concerns that need to be addressed.

Estimation. Although administrations are not usually what we mean by cross- sections, according to Brace and Hinckley (1991, 1992), studies dealing with administrations (e.g., those focusing on presidential approval) have often used pooled time-series methods to analyze variation within and between administrations (see also Mueller 1970; Ragsdale 1984). The reason is that there are significant differences in policy between administrations (particularly defense policy such as Reagan's buildup or Nixon's cutbacks). There is also reason to expect administrations to share common trends and cycles in approval and foreign policy behavior over the years (see Quandt 1988). In other words, there are compelling factors for pooling both within and across administrations. Since one of the main relationships we want to assess is that between approval and defense prime contract awards over time, we employ the pooled time-series approach.

Pooled time-series modeling is a powerful means of analyzing phenomena that vary over space and time, i.e., "where one can only be understood with explicit reference to the other" (Stimson, 1985: 915). In order to capture the effects of economic and political factors on defense contracting we must be able to look within administrations over time.

When pooling cross-sectional and time-series data, violations of the classical regression assumptions are very likely (Burkhart and Lewis-Beck 1994). Accord- ing to Stimson (1985: 919), autocorrelation and heteroskedasticity are virtually

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"inherent" in panel data. Our diagnostic tests reveal evidence of significant heteroskedasticity (ARCH test x2 = 109.77, 108.26, 108.2 with 1 degree of freedom) and autocorrelation (D.W = 0.16, 0.18, 0.18; p = 0.92, 0.91, 0.91). Therefore, we employ Kmenta's (1986: 618) method which he calls a "cross-sectionally het- eroskedastic and timewise autoregressive model." The method is explained below.

We first estimate the model by Ordinary Least Squares (OLS) and obtain estimated residuals eit. Then we use the residuals to compute the estimates of the Pi to transform the observations. We apply OLS to the transformed model. The error variances and covariances are estimated from the regression residuals of the transformed model. Finally we run Generalized Least Squares (GLS) regression by using the error variances and covariances (Kmenta 1986: 618-22).

Simultaneity bias. It is possible that our model may overlook a simultaneous relationship that would bias estimation. For example, high unemployment causes presidential approval to decrease and the President could use PCA to reduce unemployment. As a result of increasing PCA, unemployment may go down, which in turn leads to an improved approval rate. In order to test for such a situation, we employ the Hausman specification test for simultaneity (see Pindyck and Rubinfeld 1998: 353-7). The result of the Hausman test indicates that there is no simultaneity between these variables.5

Multicollinearity. Another methodological concern stems from potential multicollinearity between approval and unemployment. However, the correlation coefficient between APPROVAL and UNEMPLOYMENT is -0.55 which is well below the multicollinearity threshold of 0.80 suggested by Judge et al. (1988: 868). SHAZAM 7.0 was used for all estimations.

FINDINGS

The results of the empirical analysis are reported in Table 1. The model per- forms well in each specification. Looking first at the domestic variables, the impact of presidential approval on PCA is negative and significant.6 As the referendum model posits, the decline of presidential approval indeed brings an increase of PCA. The President is interested in maintaining approval in order to shore-up his ability to be successful in Congress and shape public and media agenda.

5 For detailed explanation of this method, see Pindyck and Rubinfeld (1998: 353-55). 6 While the coefficients for APPROVAL seem relatively small in each model (-12.2, -10.8, -10.8) compared to some other independent variables, upon standardizing of the estimates, the impact of approval is actually greater than that of the other variables. According to Welch and Comer (1988: 247), standardized coefficients are particularly useful "if the independent variables are measured in different units and if you wish to compare the relative impact of each independent variable." Stan- dardized coefficients for APPROVAL in each model are -0.956, -0.845, -0.846 and are greater than any other variables in the model. The results of standardized coefficients are also reported in Table 1. While the unstandardized approval coefficients are rather small, it must be kept in mind that their impact is continually felt over time-unlike elections or other dummy variables.

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TABLE 1 ESTIMATES OF POOLED ANALYSIS

Variable Model 1 Model II Model III

Dependent Variable: Quarterly Defense Prime Contract Awards (N = 160)

Presidential Approval GLS coefficient

(standardized coefficient) -12.2 (-0.956) -10.8 (-0.845) -10.8 (-0.846) standard error 3.72 3.44 3.44 t-statistic -3.29** -3.15** -3.15**

Unemployment 638.4 (0.137) 553.6 (0.119) 552.2 (0.118) 237.6 222.1 222.1 2.69** 2.49** 2.49**

War Involvement 1403.0 (0.187) 1358.5 (0.641) 1359.9 (0.642) 594.6 547.9 547.8 2.36* 2.48** 2.48**

Reagan Administration 8662.4 (0.241) 8357.1 (0.233) 8341.6 (0.232) 1670 1680 1686 5.19** 4.98** 4.95**

Presidential Reelection 1271.4 (0.082) 479.7 2.65**

All Presidential Elections 3.83 (0.002) 27.3 0.14

All National Elections 0.005 (0.001) 0.13 0.04

Constant 6726.3 7604.4 7634.3 1771.0 1684 1688 3.79** 4.52** 4.52**

D.W 2.04 2.09 2.09 R2 0.56 0.56 0.56

*significant at 0.05 level, one-tailed. **significant at 0.01 level, one-tailed.

A rise in unemployment leads to increases in PCA. This result confirms the earlier findings (Griffin, Wallace, and Devine 1982; Mintz and Hicks 1984; Mintz, Huang, and Heo 1992) that the President utilizes PCA as a countercyclical management tool.

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In terms of electoral cycles, the impact of presidential reelection is positive and significant, which indicates that Presidents utilize PCA to maximize incum- bency benefits. Neither all presidential elections nor national elections were significant. This finding undermines the classic PBC model that gives relevance to off-year elections.

The Reagan coefficient was positive and highly significant. The Reagan years were a time of huge increases in defense procurement as the administration rein- vested in the military-industrial complex (Farrell 1997; Mintz 1992). War involvement is also a significant determinant of PCA as expected.

There is considerable overlap in the tenets of the PBC and referendum models. Each model recognizes the importance of the economy We argue that it is the referendum model that better accounts for the relevance of the economy to PCA awards at all points during the administration. In turn, economic conditions shape approval, which in turn determines the President's ability to set agenda and achieve policy effectiveness. It is important to keep in mind that PCA do react to presidential reelections as both models predict.

CONCLUSION

We have specified and tested an empirical model of defense contracting on presidential administrations between 1953 and 1992 combining the PBC and the referendum approaches. The referendum explanation is slightly richer as it better accounts for variation in defense contracting. The model advances our under- standing of the politics of the defense budget. The findings reflect earlier evidence of a counter-cyclical component to the defense budget (e.g., Cusack 1992; Griffin, Wallace, and Devine 1982; Mintz and Hicks 1984; Mintz, Huang, and Heo, 1992; Nincic and Cusack 1979). Presidents time PCA to coincide with peri- ods of high unemployment and reelections.

We also found that Presidents are likely to shore-up their approval rate when needed rather than only at election time. According to Zuk and Woodbury (1986: 463), defense spending is not just used for the purpose of winning elections. They write "[the PBC] if it exists at all, could be less important or more complicated than once thought." We agree that it is indeed more complicated than the correlation between defense spending and electoral cycles. Our empirical analysis reveals that as approval dips the President increases the amount of PCA to improve public support by providing more jobs and boosting wages. As the referendum model posits, Presidents can utilize public resources to improve political standing throughout the term rather than only at election times. This is an important finding because pre- vious studies have only considered electoral cycles with respect to presidential manipulation of public resources for political purposes.

We contend the referendum model explanation of defense contracting will be valid for years to come. Today the President's chief duty is economic stewardship (Kernell 1997: 232). Furthermore, the ever-weakening party system means

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presidential incumbents are increasingly on their own, and presidential success in Congress is tied to approval (Rivers and Rose 1985). Left to their own devices, Pres- idents now go directly to the public by creating media events and pump-priming the economy with any available means. This scenario is played out against a back- drop of polling data and intense media attention-i.e., a perpetual election (see Marra, Ostrom, and Simon 1990). The referendum model provides a cogent explanation of the political calculus behind defense contracting decisions.

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Received: September 21, 1999 Accepted for Publication: April 18, 2000 [email protected] [email protected]

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defense contracting and domestic politics

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