Three Essays in the Dynamics of Political Behavior

Getting Settled in Your New Home: The Costs of Moving on Voter

Introduction

A voter whose place of residence has changed must register again to vote with her new address and find out where her new polling station is, which creates an administrative burden. She eventually settles into her new home, transforms into a "stayer," and overcomes the damaging shock of moving into political participation.

Literature

Some also document that they are more likely to be non-white (McDonald, 2008) and more highly educated (Squire et al., 1987). The policy idea is actually first proposed in Squire et al. (1987) in discussing how to increase turnout and also briefly discussed in Wolfinger and Highton (1995) and Highon and Wolfinger (1998).

Table 1.1: Annual Geographical Mobility Rates, By Type of Movement: 2013-2018 does it mean for a voter to have changed residences? 2 They are likely to be younger and renters (Squire et al., 1987; McDonald, 2008)

Data and Context

The voter database is provided by the Orange County Registrar of Voters (OCROV) in California. But even if the old and new addresses are similar, if I see in the USPS records that the voter has requested a change of address, I can be sure that there is a genuine change of residence.

Dynamic Impact of Moving

The voter moved within the same polling station and with the same polling station, labeled Same Precinct (5.7%);. This means if a voter crosses a polling station line or more, even within the same precinct, a turnout recovery is documented.

Figure 1.2 shows the relationship between residential stability and turnout by each information cost category, holding other covariates fixed

Mitigating Re-registration Costs: Policy Evaluation

In Orange County, the last automatic NCOA voter registration was conducted on July 26, 2018, up to movers who moved before June 15, 2018, as the Secretary of State's office receives and distributes NCOA data mid-month. So why is the effect so large, compared to previous findings of the GOTV literature.

Figure 1.5: NCOA Mailing of Orange County, California, Front and Back This policy, henceforth NCOA automatic voter registration or NCOA treatment for simplicity, 20 serves two purposes

Discussion

This is because the variance in the data increases as selection intensifies. 24These are, in order of leap date, Rhodes Island (21 January), Alaska and Oregon (24 January), Iowa and New Mexico (25 January), Colorado, Minnesota, Oklahoma, South Carolina, South Dakota and Utah (26 . January), Arkansas, Louisiana, Wisconsin and Wyoming (January 27). On a more positive note, note that the first of the breaks selected by the spline method is also 1898.

Hidden Donors: Analyzing the Censoring Problem in U.S. Federal

Introduction

Consequently, there has been a large amount of academic research on campaign finance, particularly campaign spending, in the US. Although an essential part of the data generation process, the problem of censoring and hidden donors was not adequately addressed in the campaign. financial literature (Key, 1964; Francia et al., 2003; Barber, 2016a; Magleby et al., 2018). Hidden donors are likely to become more important for researchers to study in the near future as more candidates are attracting individual donors and positioning themselves as not.

Past Research

For example, Verba et al.(1995) show that the percentage of family income contributed to political campaigns increases with household income, rising sharply at $50,000 or more (see also Wilcox(2008) and Malbin(2013)). Johnson (2010) and Culberson et al. (2018) tackle the issue using total amounts reported at the campaign level and conclude that small donors are linked to more ideologically extreme candidates, although there is some mixed evidence with this argument (Malbin, 2013) ). The most recent work that has systematically compared visible and hidden campaign contributors is Magleby et al.

The Censoring Problem in Campaign Finance Data

In March 2016, it was further reported that the campaign only had two more traditional fundraisers (Gaudiiano,2016). That the 94% is calculated before mid-May can be inferred from the Wayback Machine's snapshot of the site, the first snapshot of which is on May 21, 2016, showing the claim of 94%. Note that the total number of unified contributions is not the same as the sum of funds contributed by hidden donors, as the first $200 from visible donors is still marked as unified, and is not retroactively corrected.

Data

We then augmented the records with geographic identifiers, such as congressional district information, after geocoding each record.12 We also used record linkage to link donations that came from the same individual. We use exact first, last, and street matches and allow matches if there are differences in these variables, but employer and occupation are exactly the same for consecutive contribution records. Each interim contribution should be checked against the target committee reports to eliminate duplicate entries that will have the same contribution amount, date and personal information.

Who Are the Hidden Donors?

This indicates a difference in age groups: that the hidden donors are probably younger. In addition, visible donors are more likely to report being lawyers and doctors, while the hidden donors are slightly more likely to be teachers. However, it is also interesting to note that the proportion of visible donors reporting unemployment is slightly higher.

Table 2.2: Demographics and Occupations of Visible and Hidden Contributors, 2016 Sanders Campaign

Differences in Contribution Patterns

While visible donors give long before the primaries, hidden donors come in just before the primaries start. Distinguishing between the different types of visible donors can be important for understanding differences in their political behavior from hidden donors. Each class is a formidable force in the financial electorate, but it is the gradually visible donors who filled the presidential candidate's campaign coffers.

Figure 2.2: Distribution of Contribution Sum to Sanders, Visible and Hidden Con- Con-tributors, Truncated at $500

Conclusion

For each of the time periods, I use the following events while looking for possible breaks: (1) Republican and Democratic primary debate dates for the pre-primary period,17(2). The only legal requirement is that this removal be carried out 90 days before the date of the federal election. Note that the use of the NCOA data is not mandatory.3 The NCOA processing is just one example of a potential list maintenance activity that could be carried out by the States.

Donation Dynamics: Do Critical Campaign Events Influence

Introduction

The timing of individual contributions is a critical component to the why question, as it can help better establish the empirical model of. So in this paper, I approach this why question by looking at when these individual contributions to the presidential race take place, using nonparametric and semiparametric methods. The general rough estimates show that there is certainly a dynamic element to underlying political interest during an election cycle.

Literature

The most prominent of the studies dealing explicitly with the motivation of presidential donors, Brown et al. (1995), classify motivations into three: intentional, solidarity and material. Since there are dynamics in campaigning, it is hard to imagine that the expressive utility of giving is constant. What is interesting is that whether a donor is instrumental or expressive spur-of-the-moment, both will respond to the same critical events in the campaign.

Data and Methodology

Why should there be any momentum, overestimation or underestimation of a candidate's basic viability. To test for known events, I not only run the splicing method as is—that is, assuming all breaks are unknown—but also run the method a second time, with the jump directly modeled into the unpenalized space of partial splicings. . 14 I can also directly model these covariates in unpenalized covariate space, but that's it.

Table 3.1: Key Campaign Finance Statistics by Candidate

National Jumps

I divide the election cycle into three periods where the dynamics are different: the pre-school period, the primary period and the post-school period. Iowa caucuses, New Hampshire primaries, Super Tuesday, Super Tuesday II,18 and Acela Primaries19, dates when presumptive nominees appeared20 and convention end dates for the primary period, and (3) general election debate dates and October 7, 2016, for mail -primary period, when Access Hollywood videotapes of Trump surfaced in the Washington Post and WikiLeaks released the Podesta emails, a rare date when major scandals for either party's presidential candidates occurred. Although the selection of these events is not based on any existing measures, it spans key events on which media coverage of horse racing was focused.

Figure 3.6: National Estimate by Candidate

Initial Primary Victories and Surprise Victories

One exception is Kasich donors in five states: Connecticut, Florida, New York, Texas, and Virginia, all of which experienced a positive jump on February 8.23 Again, this means there was an increase from the day of the New Hampshire Conference. primarily self. 23There is also a case where the sum of contributions from Trump supporters in Illinois showed a slight increase on April 19, 2016, the date of the New York primary, in which Trump won a major victory in his home state. Second, the campaign finance is simply a real-time reflection of the rising popularity of these candidates—that is, there is endogeneity, but somehow a rift happened.

Local Events: In-state Wins or Losses

Clinton always led the few polls in Oregon26, but Sanders declared victory in Oregon by 12 percentage points. The different results for Trump are also difficult to interpret — these states are not easy to cluster based on covariates such as delegate size, primaries timing, Trump's popularity, and so on. This indicates that I must further have resources to choose one of the known jumps if two jumps are close to each other and are not compatible.

Events Unknown A Priori

The Trump campaign had done quite poorly in fundraising prior to June, in which they had just $1.3 million on hand. Second, for the number of Trump campaign contributions, I also observe three sets of decreases, each on July 1 (six states, ± 1 day), August 25 (eleven states, ± 1 day), and November 4 (six states). . Finally, as shown in Figure 3.10, there are declines in the amount of contributions from Sanders donors from May 4 to May 15 in nineteen different states.

Figure 3.10: All Detected Breaks by Candidate and State, Contribution Sum

An Early Look into the 2020 Data

Note in Figure 3.14 that Trump had a few days around the day the impeachment was announced and around the day the impeachment began with a very high contribution amount. In fact, the day his campaign brought in the most in both total and count was December 18, 2019, when the impeachment formally began (over $900,000). Now, because this data set does not include observations after Super Tuesday and after the Democratic field has thinned down to a single candidate, we can see spikes at the national level later in the election cycle.

Figure 3.12: National Primary Polls by Party, FiveThirtyEight, 2020 (Selected Candidates)

Conclusion

Finally, I performed the same check on the daily aggregate data at the national level for the 2020 presidential election using data collected through March 1, 2020. It remains to be seen whether there will be structural breaks later in the cycle after Super Tuesday, or in the chaos of the COVID-19 pandemic. Smoothing spline gaussian regression: more scalable computation via efficient approximation. Journal of the Royal Statistical Society: Series B (Statistical Methodology.

Legislation Related to Voter Registration

If postal service change of address information indicates that the voter has moved to a new residential address in California, the notice to be forwarded will essentially take the following form: If postal service change of address information received through a non-forwardable mailing indicates that a Voter has moved and has not left a forwarding address, a forwardable message will be sent in mainly the following form: Your data will be used to provide you with mail forwarding and change of address services.

Data Wrangling

This includes the following limited circumstances: at a congressional office on your behalf; financial entities related to financial transaction issues; Information in the US will also be provided to USPS licensed service providers to perform the mailing list correction service of lists containing your old name and address. A list of these licensed service providers can be obtained at the following URL: https://postalpro.usps.com/.

Descriptive Statistics

Regression Results in Main Text, Full Table

A person prohibited from acting as a conduit under paragraph (b)(2)(ii) of this section must return the earmarked contribution to the contributor. The report to the recipient nominee or authorized committee must be made when the earmarked contribution is sent to the recipient nominee or authorized committee pursuant to 11 CFR 102.8. iv). The information specified in paragraphs (c)(2)(ii) (A) through (C) of this section must be specified on Schedule A attached to the report for the reporting period in which the earmarked contribution is received.

Table A.3: Generalized Additive Model Results, Full Sample

Hypothetical Examples of Campaign Contributions

Although Gilbert's contribution pattern is the same as Ruby's, in that he contributes through an intermediary board, each of his records will be parsed. Gilbert has twenty-four transactions of $5 each with appropriate year-to-date aggregates clearly identified as earmarked contributions in the interim committee report. It is difficult to draw conclusions about the true state of the world from observed transactions alone.

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Demographics and Occupations of Donors

Comparisons with Primary Winners

Classical Calculations of Breakpoints

Having tested the Nile data with the spline method, we will now test the Bush poll data, the first example in Ratkovic and Eng (2010), with the classical methods, to see if they also include the two ruptures in the September 11 attacks. and the beginning of the invasion of Iraq, as well as the spline method in Figure C.3. However, the segmentations do not seem to be an accurate summary of the Bush Poll's behavior and miss the most obvious breaks. We conclude that we cannot easily judge the “superiority” of one method over another because they are simply based on different assumptions about the underlying process of the data and have different strengths.