The Shift in Suburban Voting Patterns: A Closer Look at Nassau and Rockland Counties in New York

During the 2020 United States presidential election, the political landscape in suburban New York saw a significant shift. Specifically, Nassau and Rockland Counties, both historically supportive of Hillary Clinton in 2016, supported Donald Trump in 2020. However, this apparent shift only held until the final count, revealing a different picture as the mail-in ballots were processed. This article delves into the reasons behind this change and the implications of the final results.

Election Night vs. Final Count

On election night, both Nassau and Rockland Counties appeared to be leaning Republican. The in-person vote, which was counted first, favored the Republican candidate. This was reflected in the initial electoral results, where Donald Trump was leading Joe Biden by comfortable margins in both counties. In fact, on election night, Biden was only slightly ahead of Trump in New York as a whole, with a margin of 12–13 percentage points.

Specifically, Nassau County showed a very slight lead for Trump, with a margin of around 1 percentage point, while Rockland County appeared to be leaning more heavily towards Trump, with a margin of about 11 percentage points. However, as the mail-in ballots were counted, the trend shifted dramatically, leading to a blue wave in both counties.

Political Dynamics at Play

The final count revealed a much different picture. Trump saw a significant drop in his share of the vote, with his support in New York declining from 43–44% on election night to a final total of 38%. Conversely, Biden's share increased, from 55% on election night to 61% in the end. The majority of the shift came from the increase in mail-in ballots, which favored Democratic voters more heavily.

Nassau County saw Biden's share increase by 3.8 percentage points compared to Hillary Clinton's 2016 performance, while Rockland County improved by 4.5 percentage points. While Rockland County may have experienced a closer race due to Orthodox Jewish support for Trump, this alone cannot explain the significant shift. Rockland County has the highest per capita Jewish population in the US, with 31.4% of its residents identifying as Jewish, but this does not fully account for the shift.

Potential Reasons for the Shift in Nassau and Rockland Counties

The shift in voter support from Hillary Clinton to Donald Trump was likely influenced by several factors. These include, but are not limited to:

Shifts in Demographics: Changes in the demographic makeup of the counties can influence voting patterns. As the population shifts, so do voting preferences. Economic Factors: Economic conditions play a significant role in election outcomes. Local economic policies and national economic trends can sway voter support. Policy Positions: Differences in policy positions, particularly on issues such as health care, education, and social welfare, can lead to shifts in voter support. Trust in Institutions: Trust in government and political figures can significantly impact voter behavior. Changes in trust levels can lead to shifts in support.

Suburban America's Changing Landscape: Suburban areas are often seen as 'swing' regions, where neither party has a clear advantage. The 2020 election saw a dramatic shift in this narrative, with suburban counties that traditionally supported the Democratic Party swaying towards Trump due to a combination of the above factors. However, with the final count, these regions leaned heavily Democratic, indicating a return to the typical voting patterns of these areas.

Conclusion

The political dynamics in Nassau and Rockland Counties during the 2020 election highlight the complex and evolving nature of voter support. While the initial returns showed a shift towards the Republican candidate, the final count revealed a significant Democratic advantage. This underscores the importance of comprehensive mail-in ballot counts in election results and the need for a deeper analysis of the underlying factors that influence voter behavior.