Be Careful what You Count: Updating Legislative Turnover in the 50 States

Abstract

Legislative turnover is indicative of political careerism, district competitiveness, and the strength of the incumbency advantage. Although there are many examinations of legislative turnover in U.S. state legislatures, there has not been an update in nearly 2 decades. One limitation of the existing turnover measures is the inability to distinguish between naturally occurring turnover and the artificial turnover caused by term limits. In this research note, I present an update to legislative turnover from 2002 to 2018 and discuss the importance of using updated data, as well as avenues for future research.

Keywords

state politics legislative politics legislative turnover data measurement term limits

Turnover is influenced by a number of different factors including institutional rules and electoral restrictions (François & Grossman, 2015; Matland & Studlar, 2004; Maestas, 2000; Rosenthal, 1974; Shin and Jackson III, 1979), and is used to assess phenomena including electoral stability and legislative capacity (Moncrief & Thompson, 2001; Uppal & Glazer, 2015; Woods & Baranowski, 2006). More recent research utilizes turnover levels to help understand gender and minority representation within the legislature (Arceneaux, 2001; Darcy & Choike, 1986; Reingold, 2012, 2019). Turnover is associated with legislative careerism (Habel, 2008; Moncrief et al., 2004), legislative behavior (Kerby & Blidook, 2011; Kirkland, 2014; Uppal & Glazer, 2015), and even has ties to democratic legitimacy (François & Grossman, 2015). Measures of turnover are also routinely used as a control in studies of the state legislature where turnover is not the primary interest (Maestas, 2000; Makse, 2019; Melusky, 2018; Stonecash, 1999; Shay, 2020).

Legislative turnover is typically a measure of the number of seats vacated each year or session. The turnover measure presented by Moncrief et al. (2004) is commonly used by scholars to examine the causes and effects of turnover, but the data end in 2002. Since the implementation of term limits in 15 states, this measure turnover is no longer representative of what is occurring in the legislature. In this research note, I update legislative turnover from 2002 through the 2018 election. I present two different measures of turnover, one which takes into account the artificial turnover caused by term limits. In addition to presenting the average rate of turnover for all 50 states, yearly data will be made publicly available. I discuss the use of each measure of turnover and present a brief replication analysis before discussing avenues for future research.

Updating Turnover

Given the ever-changing dynamics in state politics, it is important to understand how many long-held truths hold up over time. It would be misleading to continue to fall in line with early research on turnover from Rosenthal (1974), Shin and Jackson III (1979), Niemi and Winsky (1987), Fett & Ponder (1993) the first of which is nearly 50 years out of date. Table 1 lists some of the key studies where turnover is of primary interest, including studies where the motivation was to assess legislative turnover and the changes that have occurred. Many of these studies build from each other. For example, Niemi and Winsky (1987) add data to what was originally compiled by Shin and Jackson III (1979). Similarly, Krupnikov and Shipan (2020) and Uppal and Glazer (2015) use data from Moncrief et al. (2004) and Moncrief et al. (2008), respectively. Even though there have been recent examinations of legislative turnover, the data remain out of date.

Table 1.

Studies Where Turnover is the Primary Interest.

Author	Years of Interest	Unit of Measurement	Number of States
Hyneman 1938	1925–1935	State/Chamber	10
Rosenthal 1974	1963–1971	State/Chamber	50
Shin and Jackson 1979	1931–1976	State/Chamber	50
Niemi and Winsky 1987	1971–1985	State/Chamber	50
Moncrief et al., 2004	1982–2002	State/Chamber	50
Uppal and Glazer 2015	1980–2007	State	50
Krupnikov & Shipan 2020	1982–2000	State	50

In order to demonstrate the differences that have occurred in legislative turnover across time, Table 2 compares the 2002–2018 update to the data from Moncrief et al. (2004). The new data are from the Book of the States 2003–2019 editions.¹ Accounted for in this table are the 15 states with term limits (noted in italics), which are: Arizona, Arkansas, California, Colorado, Florida, Louisiana, Maine, Michigan, Missouri, Montana, Nebraska, Nevada, Ohio, Oklahoma, and South Dakota. Recently, turnover has not been assessed by the legislative chamber, as they are assumed to be so similar (See Squire & Hamm, 2005). However, most early examinations of turnover looked at each chamber independently as it would be remiss to overlook the differences that do exist, that is, chamber size, length of service, term limit constraints, and even district type. Given the differences that exist, I present the average rate of turnover by legislative chamber.

Table 2.

Historical Overview of Average Turnover Rates.

State	Lower Chamber			Upper Chamber
State	1981–1990*	1991–2000*	2002–2018	1981–1990*	1991–2000*	2002–2018
Alabama	35	31	9	38	40	9
Alaska	39	32	16	24	28	11
Arizona	25	37	23	23	33	21
Arkansas	14	32	19	15	21	12
California	16	40	18	11	28	14
Colorado	30	34	19	23	29	16
Connecticut	24	20	10	30	18	9
Delaware	15	13	10	10	10	6
Florida	22	32	17	21	27	14
Georgia	18	19	11	18	23	11
Hawaii	24	23	10	17	25	8
Idaho	27	22	14	25	19	11
Illinois	15	22	11	14	16	10
Indiana	17	16	9	16	11	7
Iowa	22	26	12	16	20	11
Kansas	22	25	15	25	43	11
Kentucky	18	21	10	23	18	7
Louisiana	29	29	9	25	38	10
Maine	35	37	21	26	38	20
Maryland	32	35	10	28	29	9
Massachusetts	17	19	8	19	19	8
Michigan	20	30	23	31	30	20
Minnesota	22	20	13	25	21	10
Mississippi	33	24	8	36	29	10
Missouri	20	22	18	13	18	16
Montana	30	35	20	23	25	16
Nebraska	-	-	-	21	20	15
Nevada	35	29	19	24	14	13
New Hampshire	37	34	22	29	34	19
New Jersey	26	24	11	27	29	7
New Mexico	23	24	11	37	33	7
New York	15	14	9	11	11	9
North Carolina	25	24	13	27	23	14
North Dakota	28	22	9	17	16	8
Ohio	17	26	16	18	24	14
Oklahoma	28	17	16	17	10	15
Oregon	25	36	14	20	28	10
Pennsylvania	14	11	9	11	12	7
Rhode Island	21	19	10	22	20	7
South Carolina	20	22	9	30	20	6
South Dakota	28	39	21	27	32	22
Tennessee	18	16	12	16	15	10
Texas	23	17	11	19	16	7
Utah	31	29	13	21	26	11
Vermont	27	30	13	29	25	10
Virginia	19	18	8	23	24	8
Washington	28	32	12	16	22	11
West Virginia	40	28	14	29	21	12
Wisconsin	23	17	11	21	15	10
Wyoming	24	25	15	23	26	10
Total	24	25	13	22	23	11

Note: States in italics currently have legislative term limits. * Historical data are from Moncrief et al. (2004).

The average rate of turnover for all states from 2000 to 2018 is 13% in the lower chamber and 11% in the upper. Moncrief et al. (2004) found that from 1991 to 2000, the average rate of turnover was 23% in state senates and 25 in the lower chambers, and only six states had an average below 15% (2004, 365). This update reveals that the average rate of turnover decreased in 98 of the 99 state chambers from the 1991–2000 period to 2002–2018. In some instances, like Alabama and New Mexico turnover declined by more than 25%. Even in states that have legislative term limits, there is a noticeable decline in the average rate of turnover.

Using an out of date measure of turnover can lead to incorrect assumptions about what is occurring in the legislature. There was very little change in the average turnover rate from 1981 to 1991, which is likely why the latter measure is still used to examine turnover. This update demonstrates an evident decline in turnover with the average of all states dropping by more than 10% and a total of 36 states have an average turnover rate below 15%. Over time, turnover has continued to decline, and the Moncrief et al. (2004) measure is no longer an accurate indicator of turnover in the states.

The Two Types of Turnover

There are two types of turnover that occur in state legislatures, natural and artificial, which collectively make up the total turnover rate. Naturally occurring turnover is the expected rate of turnover that is a result of election loss, resignation, and even retirement. These natural causes of turnover are a result of a lawmaker pursuing a career in the legislature and making her own career choices. Different from natural turnover, artificial turnover is a result of forced turnover that removes the ability of a legislator to make her own decision. In the U.S. context, artificial turnover is a direct result of having legislative term limits where many lawmakers are forced from office and are unable to make that decision for themselves.

This idea of two forms of turnover is not new. After the passage of term limits, Francis and Kenny (1997) noted that there would eventually be different types of turnover as a result of term limits. Even though term limits have been in place for 20 years in some states, the differences in legislative turnover have remained largely unexplored. Artificial turnover exists in only 15 states and implies that legislators were not given the choice to return and, instead, were forcefully removed from office because of term limits. In contrast, natural turnover is present in all states as members cycle through the legislature.

Table 3 contains the average rate of natural turnover for each chamber from 2002 to 2018 and the rate of total turnover.² This measure of natural turnover captures changes that are solely a result of natural causes, that is, election loss, resignation, and retirement. This distinction between natural and artificial turnover only applies to states with term limits. The rate of natural turnover and total turnover for the entire legislature is the same in all states without limits because there is no artificially induced turnover. For states with term limits, the discrepancy between the natural turnover rate and the total turnover rate is the percentage of people who left as a result of term limits. For example, in Maine, there is a decline from total to natural turnover by 7%, and in California and Arizona, this difference is upwards of 10%.

Table 3.

Average Percent of Turnover by State, 2002–2018

	Natural Turnover (-Artificial)			Total Turnover
State	Lower Chamber	Upper Chamber	Both Chambers	Both Chambers
Alabama	9.08	9.24	9.12	9.12
Alaska	15.59	10.88	14.02	14.02
Arizona	17.06	14.12	16.11	21.99
Arkansas	7.47	5.71	7.02	17.04
California	6.64	4.53	5.94	16.46
Colorado	12.76	7.06	10.76	18.18
Connecticut	9.87	8.66	9.62	9.62
Delaware	9.90	6.16	8.63	8.63
Florida	8.92	6.32	8.27	16.03
Georgia	10.92	11.24	10.99	10.99
Hawaii	10.15	8.00	9.44	9.44
Idaho	14.12	11.26	13.17	13.17
Illinois	10.67	9.57	10.30	10.30
Indiana	9.06	7.29	8.47	8.47
Iowa	12.00	11.18	11.73	11.73
Kansas	15.01	10.74	13.98	13.98
Kentucky	9.53	6.66	8.74	8.74
Louisiana	5.71	6.33	5.88	9.27
Maine	13.44	12.10	13.19	20.65
Maryland	10.22	8.51	9.79	9.79
Massachusetts	7.46	7.94	7.56	7.56
Michigan	9.89	3.95	8.36	22.13
Minnesota	13.39	10.54	12.44	12.44
Mississippi	7.47	9.73	8.15	8.15
Missouri	7.98	5.36	7.52	17.42
Montana	12.94	6.12	10.67	18.47
Nebraska	.	5.76	5.76	15.0
Nevada	16.95	10.08	14.66	16.99
New Hampshire	21.50	18.63	21.34	21.34
New Jersey	10.96	6.76	9.56	9.56
New Mexico	11.43	6.72	9.66	9.66
New York	9.29	8.75	9.14	9.14
North Carolina	12.65	13.53	12.91	12.91
North Dakota	8.76	8.26	8.59	8.59
Ohio	9.27	5.88	8.42	15.78
Oklahoma	10.08	9.31	9.83	15.40
Oregon	14.22	10.20	12.88	12.88
Pennsylvania	8.49	6.94	8.18	8.18
Rhode Island	10.43	7.12	9.32	9.32
South Carolina	9.20	6.14	8.37	8.37
South Dakota	15.13	15.63	15.29	21.18
Tennessee	11.47	10.16	11.14	11.14
Texas	10.55	7.02	9.94	9.94
Utah	13.25	10.55	12.50	12.50
Vermont	12.47	10.20	12.09	12.09
Virginia	8.47	7.79	8.28	8.28
Washington	11.46	11.04	11.32	11.32
West Virginia	14.00	11.59	13.39	13.39
Wisconsin	11.17	9.80	10.83	10.83
Wyoming	14.71	10.39	13.27	13.27
Total	11.30	8.96	10.54	12.76

Note: States in italics currently have legislative term limits.

Figures 1 and 2 illustrate the differences that exist between total and natural turnover. A darker block indicates a higher rate of turnover. In Figure 1, the darkest shaded states are all those that have term limits, aside from New Hampshire.³ However, in Figure 2, there are very few states that are dark. In fact, term-limited states like Nebraska, California, and Louisiana appear to have lower turnover than other non-term-limited state like Kansas, West Virginia, and North Carolina. Overall, these two figures illustrate that there is a noticeable difference between the two measures of turnover.

Figure 1.

Average rate of total turnover in all states, 2002–2018.

Figure 2.

Average rate of natural turnover in all states, 2002–2018

Why is it necessary to have two distinct measures of turnover? Including or excluding the artificial turnover caused by term limits can bias results. Ultimately, theory will drive the decision to use one form of turnover over another. When measuring turnover, it is important to ask if the goal is to assess the number of people leaving the legislature or the different reasons why individuals leave. Studies that utilize turnover as a predictor for large-scale behavior ought to consider the theoretical implications of looking at all turnover versus natural turnover.

Using one measure in lieu of another can result in theoretical bias. In some instances, including the artificial turnover caused by legislative term limits can inflate results, especially when looking at career motivations, legislator representation, or policy responsiveness. It would be inaccurate to include artificial turnover if turnover were being used to examine constituent satisfaction with their legislators. In other examinations of turnover, the focus will be on how many people are leaving, regardless of why; in this instance, the total rate of turnover is sufficient.

To illustrate the differences between the two types of turnover, I replicate part of Todd (Makse, 2017) analysis of state legislative committee retention.⁴ His analysis is centered on evaluating the effects of committee retention on bill referrals and passage rates in 13 states, five of which have term limits. For replication purposes, I follow his analysis of bill referrals (Table 3, page 429). Makse utilizes a measure of observed turnover in the legislature to help account for overall stability within the legislature. While Makse’s use of observed turnover is valid for his theoretical argument, it is possible that there could be an alternative theory to account for those states that have term limits.

Under the premise of an alternative theory, it could be argued that there needs to be another analysis evaluating those legislators who choose to leave the legislature versus those who are forced out. Put another way, an alternative theory may propose that there is an inherent difference in the committee retention of states with term limits and those without, which can in turn influence the relationship between committee retention and bill referrals. Therefore, using natural turnover and removing those who do not have a choice is a better approach based on this new theory. I duplicate Makse’s original findings and replicate them using the new measure in Table 4. In the original study, Makse found, turnover did affect the relationship between committee retention and bill referrals (Model 1). Further, in an analysis using interaction terms, the relationship between retention and referral was conditional on both professionalization and turnover (Model 2). However, looking at columns 2 and 4, the results do not hold up when using an updated measure of only natural turnover.

Table 4.

Replication of (Makse, 2017) Committee Bill Referrals (Table 3).

	Model 1	Natural Turnover	Model 2	Natural Turnover
	(Makse)	(Replication)	(Makse)	(Replication)
Committee-level covariants
Committee retention %	0.610***	0.531***	0.644***	0.528***
Committee retention %	(0.155)	(0.158)	(0.136)	(0.153)
Chair of committee unchanged	−0.013	−0.019	−0.017	−0.017
Chair of committee unchanged	(0.048)	(0.050)	(0.048)	(0.050)
Jurisdiction change	−0.158**	−0.165**	−0.162**	−0.166**
Jurisdiction change	(0.065)	(0.067)	(0.065)	(0.067)
Committee size	0.008*	0.013**	0.009*	0.014**
Committee size	(0.005)	(0.006)	(0.005)	(0.006)
Committee-floor ideological distance	−0.146	−0.182*	−0.158	−0.184*
Committee-floor ideological distance	(0.106)	(0.107)	(0.105)	(0.107)
Chamber-level covariants
Chamber size	0.002	0.001	0.002	0.001
Chamber size	(0.001)	(0.001)	(0.001)	(0.001)
Aggregate change in chamber committees	0.491***	0.494***	0.438***	0.479***
Aggregate change in chamber committees	(0.158)	(0.163)	(0.159)	(0.164)
New majority party	−0.041	−0.050	−0.035	−0.042
New majority party	(0.066)	(0.069)	(0.066)	(0.069)
Majority size	−0.025	−0.105	−0.185	−0.081
Majority size	(0.530)	(0.540)	(0.533)	(0.543)
Committee autonomy	−0.027	−0.060	−0.028	−0.059
Committee autonomy	(0.083)	(0.092)	(0.083)	(0.094)
Legislative turnover	1.616**	4.128	1.654**	4.038
Legislative turnover	(0.696)	(2.949)	(0.703)	(3.014)
Legislative professionalism	1.591*	2.612***	1.159	2.577**
Legislative professionalism	(0.903)	(1.013)	(0.911)	(1.035)
Cross-level interactions
Committee retention % x turnover			−4.202***	7.522
Committee retention % x turnover			(1.485)	(7.281)
Committee retention % x professionalism			4.212**	3.254
Committee retention % x professionalism			(1.899)	(2.345)
Constant	4.192***	4.310***	4.539***	4.690***
Constant	(0.431)	(0.514)	(0.406)	(0.456)
N(Committees/Chambers)	872/28	835/27	872/28	835/27
Standard errors in parentheses

*** p < 0.01, ** p < 0.05, * p < 0.1

Centering the analysis on those legislators who have the opportunity to stay yields different results than when looking at the overall rate of turnover. When accounting for those legislators who have the opportunity to continue serving, turnover no longer conditions the relationship between committee retention and bill referrals. This replication emphasizes the importance of how theory and data must align. The theory must drive which measurement of turnover ought to be used. In some circumstances, it might be of use to estimate models using both measures to better understand how the forced turnover in states without term limits affects the results.

Discussion and Suggestions for Future Research

Since early examinations, legislative turnover has been utilized as a key explanatory variable for everything from economic conditions to legislative behavior. Current measures of turnover do not capture the historically low levels of turnover present in U.S. state legislatures. This update, through 2018, produces a more accurate measure for scholars to use. In addition, there is a secondary measure that accounts for the artificial turnover that is caused by term limits.

The differences found between this measure and the Moncrief et al. (2004) measure point to the question of how often must turnover be updated? While there was little variation from 1981–1990 to 1991–2000, there was a great deal of change from 1991–2000 to 2002–2018. These shifts suggest an update is essential at least every two decades. It appears unlikely that a major shift would occur in as little as a 10-year span, given that lawmakers are increasingly serving for lengthier periods of time.

The continued decline in legislative turnover in U.S. state legislatures indicates that incumbents remain secure and new members rarely enter office. These data can be used to examine the driving factors behind the continued low rate of turnover, as well as the implications for these rates. The two measures here can be used in different capacities based on the theoretical underpinnings of turnover. In some instances, the inflated rate of total turnover can bias results, especially when evaluating legislative careerism and the decisions that members must make. The difference between natural and artificial turnover may be less important in the examinations of policy responsiveness or legislative efficiency because it matters how many lawmakers are leaving the legislature but matters less why they are leaving.

Future avenues of research include exploring the reasons for the continued decline in legislative turnover. Has turnover declined as a result of fewer people running for office or is it because members are choosing to serve for longer, and what are the differences between these internal and external forces? There is increasingly more focus on demographic turnover; there needs to be more research on the variation of legislative diversity and whether these lower turnover rates are particular to any one group of lawmakers. Last, it is worth exploring the point at which turnover rates become too low and there are not enough new members bringing forth new ideas. At what point does the lack of turnover hinder policy development and ultimately harm the institution?

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Jordan Butcher

Notes

References

Arceneaux

(2001). The “gender gap” in state legislative representation: new data to tackle an old question. Political Research Quarterly, 54(1), 143–160. https://doi.org/10.1177/106591290105400108

Council of State Governments . The Book of the states. Council of State Governments.

Darcy

Choike

J. R.

(1986). A formal analysis of legislative turnover: Women candidates and legislative representation. American Journal of Political Science, 30(1), 237–255. https://doi.org/10.2307/2111303

Fett

Patrick

Ponder

Daniel

(1993) (In press). Congressional Term Limits, State Legislative Term Limits and Congressional Turnover: A Theory of Change. PS: Political Science & Politics, 26(2), 211-216.

Francis

W. L.

Kenny

L. W.

(1997). Equilibrium projections of the consequences of term limits upon expected tenure, institutional turnover, and membership experience. The Journal of Politics, 59(01), 240–252. https://doi.org/10.2307/2998225

François

Grossman

(2015). How to define legislative turnover? The incidence of measures of renewal and levels of analysis. The Journal of Legislative Studies, 21(4), 457–475. https://doi.org/10.1080/13572334.2015.1082311

Habel

P. D.

(2008). The consequences of electoral institutions for careerism. Legislative Studies Quarterly, 33(3), 471–494. https://doi.org/10.3162/036298008785260871

Hyneman

C. S.

(2008). Tenure and turnover of legislative personnel (pp. 21–31).

Kerby

Blidook

(2011). It’s not you, it’s me: Determinants of voluntary legislative turnover in Canada. Legislative Studies Quarterly, 36(4), 621–643. https://doi.org/10.1111/j.1939-9162.2011.00029.x

10.

Kirkland

J. H.

(2014). Chamber size effects on the collaborative structure of legislatures. Legislative Studies Quarterly, 39(2), 169–198. https://doi.org/10.1111/lsq.12041

11.

Krupnikov

Shipan

C. R.

(2020). Voter uncertainty, political institutions, and legislative turnover. Political Science Research and Methods, 8(1), 14–29. https://doi.org/10.1017/psrm.2018.32

12.

Maestas

(2000). Professional legislatures and ambitious politicians: Policy responsiveness of state institutions. Legislative Studies Quarterly, 25(4), 663. https://doi.org/10.2307/440439

13.

Makse

(2017a). Replication data for “the retention of expertise and productivity in state legislative committees”.

14.

Makse

(2017b). The retention of expertise and productivity in state legislative committees. State Politics & Policy Quarterly, 17(4), 418–440. https://doi.org/10.1177/1532440017731495

15.

Makse

(2019). Professional backgrounds in state legislatures, 1993–2012. State Politics & Policy Quarterly, 19(3), 312–333. https://doi.org/10.1177/1532440019826065

16.

Matland

R. E.

Studlar

D. T.

(2004). Determinants of legislative turnover: a cross-national analysis. British Journal of Political Science, 34(1), 87–108. https://doi.org/10.1017/s000712340300036x

17.

Melusky

(2018). Legislative pay and voluntary retirement in the american states. The Journal of Legislative Studies, 24(4), 526–545. https://doi.org/10.1080/13572334.2018.1547945

18.

Moncrief

G. F.

Niemi

R. G.

Powell

L. W.

(2004). Time, term limits, and turnover: Trends in membership stability in us state legislatures. Legislative Studies Quarterly, 29(3), 357–381. https://doi.org/10.3162/036298004x201212

19.

Moncrief

Niemi

R. G.

Powell

L. W.

(2008). Turnover in state legislatures: An update. In Annual Meeting of the Western Political. Science Association, San Diego, 2008

20.

Moncrief

Thompson

J. A.

(2001). On the outside looking in: Lobbyists’ perspectives on the effects of state legislative term limits. State Politics & Policy Quarterly, 1(4), 394–411. https://doi.org/10.1177/153244000100100404

21.

Niemi

R. G.

Winsky

L. R.

(1987). Membership turnover in us state legislatures: Trends and effects of districting. Legislative Studies Quarterly, 12(1), 115–123. https://doi.org/10.2307/440048

22.

Reingold

(2012). The uneven presence of women and minorities in America’s state legislatures—and why it matters. Scholars Strategy Network.

23.

Reingold

(2019). Gender, race/ethnicity, and representation in state legislatures. PS: Political Science & Politics, 52(3), 426–429. https://doi.org/10.1017/s1049096519000052

24.

Rosenthal

(1974). Turnover in state legislatures. American Journal of Political Science, 18(3), 609-616. https://doi.org/10.2307/2110635

25.

Shay

L. P.

(2020). Do term limits “limit” the speaker? Examining the effects of legislative term limits on state speaker power. State Politics & Policy Quarterly. https://doi.org/10.1177/1532440020947643

26.

Shin

K. S.

Jackson

J. S.

III (1979). Membership turnover in us state legislatures: 1931-1976. Legislative Studies Quarterly, 4(1), 95–104. https://doi.org/10.2307/439606

27.

Squire

Hamm

K. E.

(2005). 101 chambers: Congress, state legislatures, and the future of legislative studies. Ohio State University Press.

28.

Stonecash

J. M.

(1999). Political cleavage in us state legislative houses. Legislative Studies Quarterly, 24(2), 281–302. https://doi.org/10.2307/440312

29.

Uppal

Glazer

(2015). Legislative turnover, fiscal policy, and economic growth: Evidence from us state legislatures. Economic Inquiry, 53(1), 91–107. https://doi.org/10.1111/ecin.12118

30.

Woods

N. D.

Baranowski

(2006). Legislative professionalism and influence on state agencies: The effects of resources and careerism. Legislative Studies Quarterly, 31(4), 585–609. https://doi.org/10.3162/036298006x201940