Making Your Blue Dollar Count

How You Should Invest In Democratic Congressional Candidates

The 2024 presidential election will be extremely close, and Vice President Harris is the underdog. With less than 60 days until November 5th, a nationwide polling lead of 2–3 points, and the swing states a virtual tossup, it is far too early to write off the dangerous possibility of a second Trump presidency, even after his abysmal debate performance this week.

If (god forbid) Trump does manage to eke out a win in Pennsylvania, Georgia, and North Carolina (his most likely path to victory), control of Congress will matter immensely. With a Republican trifecta — controlling the presidency, Senate, and House of Representatives — Trump could wreak unimaginable havoc on American government and society, banning abortion nationwide, completely dismantling the civil service, derailing the fight against climate change, cutting taxes on the wealthy, destroying the Affordable Care Act, and so much more. A defanged President Trump, without a Republican Congress, would be disastrous, but not catastrophic. Without Congress, Trump cannot legislate: he could not ban abortion nationwide, nor further cut taxes for his billionaire patrons. As depressing as disaster scenario planning is, it provides powerful motivation to invest in House and Senate races, rather than only the presidential election. Democrats must play the long game, both up and down the ballot, and invest in Congress.

To that end, I’ve ranked who I believe are the best Congressional candidates that you should donate to this election cycle. I implore you, fellow Democrats, to prioritize donations to House over Senate candidates. As much as it grieves my blue heart to declare, I have much less faith in the Democratic Party’s ability to maintain control of the Senate than to flip the House. The Senate by its nature turns on a much smaller dime than the House, and the handful of tossup seats in the Senate are an uphill climb. The House is where your dollar will make the most difference because these races are small and winnable. For those who trust my (certainly flawed) judgment and are itching to invest your political dollars in promising candidates, here’s a list of my top fifteen House and top four Senate candidates. For the methodologically inclined and interested, I’ve put together a short write-up below on how I assembled the list. You can look at my full donation index spreadsheet.

House

1. John Mannion, New York 22nd
2. Derek Tran, California 45th
3. Janelle Bynum, Oregon 5th
4. Amish Shah, Arizona 1st
5. Kristen McDonald Rivet, Michigan 8th
6. Carl Marlinga, Michigan 10th
7. Adam Gray, California 13th
8. Rudy Salas, California 22nd
9. Tony Vargas, Nebraska 2nd
10. Laura Gillen, New York 4th
11. Don Davis, North Carolina 1st
12. Vicente Gonzalez, Texas 34th
13. Mondaire Jones, New York 17th
14. Curtis Hertel, Michigan 7th
15. Missy Smasal, Virginia 2nd

Senate

1. Sherrod Brown, Ohio
2. Jon Tester, Montana
3. Debbie Mucarsel-Powell, Florida
4. Colin Allred, Texas

House Methodology

The first component of my final “Donation Index,” which ranks races according to the power of your donation, is generated purely based on how competitive the race is. District-level polling is scarce this election, and the best accessible approximator of House race competitiveness is race ratings published by pundits and political analysts. I selected seven — Cook Political Report, Inside Elections, Split Ticket, Sabato’s Crystal Ball, Race to the White House, The Hill/DDHQ, and CNalysis— representing a wide range of opinion, from optimistic for Democrats (Split Ticket) to more pessimistic (Sabato). I varied the weight of each pundit in my average based on how reliable I believe them to be (see “All Rating Pundits” sheet in my spreadsheet). I then assigned each rating a numeric value (for example, I gave “Tossup” a value of 0.00 and “Lean D/R” a value of 0.25), summed the weighted values across all seven ratings, and divided them by 5, producing my “Average Rating.” I did not assign rating values linearly, instead weighing less competitive ratings (“Safe” or “Likely”) higher than more competitive ratings (“Tossup,” “Tilt,” or “Lean”). I should note that I only included House races in my main Donation Index model that have an average rating of at least “Likely D/R” or more competitive.

I then produced my “Competitiveness Score” by subtracting the absolute value of each race’s “Average Rating” from 1.5, the value of a race being rated as “Likely D/R,” and then multiplying the result by 30, which is the weight I assigned this “Competitiveness Score” relative to other variables. The final result of this component of the “Donation Index” can be found in the “Competitiveness Score” column of my spreadsheet.

The next variable I include is which party raised more money in each race relative race competitiveness. I first dug through publicly available data on the Federal Election Commission (FEC) website to catalog how much money the Democratic and Republican candidates have raised in each competitive House race. I then calculated the fundraising margin as a percent of the total money raised in each race and compared the margin to each race’s average rating (see Chart #1). From this chart, I generated a linear trendline, which estimates the expected fundraising margin at each average rating and vice versa; in other words, the trendline shows if a race has an “Average Rating” of X, then it would be expected to have a fundraising margin of Y. The “Expected Dem Cash Margin” column applies the trendline to each race. Finally, the “Cash Score” subtracts the expected fundraising margin from the actual fundraising margin, translates this percentage into a number, and weighs this variable by .9 relative to the overall mix of variables comprising the “Donation Index.”

The “Competitiveness Score” and “Cash Score” are the most important variables contributing to my “Donation Index,” though I consider three other variables. The “Small Money Bonus” represents the ‘bang for your buck,’ looking at the total amount raised for a race relative to its competitiveness. Here, I follow a similar process as for the “Cash Score,” generating a chart (Chart #2) and trendline comparing the total cost of each House election to the absolute value of its average rating. I then subtract the total raised for each race from the total amount expected to be raised based on race competitiveness (using the trendline equation). This is divided by 1,000,000 to weigh this “Small Money Bonus” to fit within the larger model, producing values that represent its importance relative to other variables.

I then added a “Swing State Bonus” to account for possible up-ballot effects from donating to House campaigns. A well-funded House race in Pennsylvania may positively contribute to the presidential race in Pennsylvania, whereas a House campaign in Louisiana, however effective, is unlikely to move the dial towards Harris in that state. As such, I assigned some relatively small values to account for such potentialities. Each state’s values in this category are listed in the “Swing State Bonus” sheet (found on a bottom tab on the spreadsheet).

The final variable I include is the smallest: the “Crossover Bonus” accounts for the potential down-ballot effects of running for House in a presidential election year. The logic is that as partisanship has increased in recent years, voters are decreasingly likely to split their votes between Democratic presidential candidates and Republican House candidates — and vice versa. As such, I distributed small bonuses to districts Biden won in 2020 that have a Republican representative by dividing Biden’s margin of victory by 10 (thus weighing it according to its relative importance in my view). Additionally, in districts Trump won in 2020 that have a Democratic representative, I divided Trump’s margin of victory by 20, giving these embattled Democrats a smaller boost compared to Biden/Republican districts (again, subjective weighing).

The sum of these variables — “Cash Score,” “Competitiveness Score,” “Small Spending Bonus,” “Swing State Bonus,” and “Crossover Bonus” — produces my final “Donation Index.”

It’s important to emphasize that my methodology is subjective. There is no way to objectively determine which races to donate to. I view this project as an attempt to integrate variables that I think are important into donation decision-making, rather than election funding purely based on “vibes.” I invite critique and scrutiny of my method, and I am open to adjusting and improving my model. Additionally, I plan on frequently updating my model in the coming months, as race ratings and spending figures change. My goal is for this to be a tool for Democrats to think about how we can donate as effectively as possible. The takeaway should be to ignore the glitzy prospect of electing an Adam Frisch, who sits at the bottom of the list with a score of -42.94, and instead bankroll the heck out of John Mannion, who tops the list with a 63.64 score.

Senate Methodology

As much as I wanted my House model to work for the Senate, and attempted to tweak it accordingly, it did not. Competitive Senate races are completely awash in Democratic money: Jon Tester (D-MT) has raised a staggering $44 million, while his Republican opponent, Tim Sheehy, has raised $14 million. As such, Democrats have raised about $51 per person in Montana. And yet, the race has an average rating of “Tilt R.” Because of the stunning Democratic cash advantage in Montana, my model would have you instead contribute to five other races before Montana.

But yes, you should donate to Jon Tester, and there is a clear logic to the (narrow) path to a Democratic Senate. The basic Senate state of play goes as follows: Democrats can count on having at least 42 seats and Republicans 48 after November, leaving a competitive field of 10 seats. Republicans need to win only 3 competitive races to flip the Senate, and two of those competitive seats are highly likely to stay red: Texas and Florida. Thus, the one remaining seat Republicans need can either come from Montana or Ohio, both of which Trump won in 2020.

As such, the Democratic donation logic should be to contribute primarily to Ohio and Montana, with Florida and Texas as a distant third and fourth place. My model, when applied to the Senate, does not tell you to do this, and, therefore, fails. Trust the logic, not the model: donate to Jon Tester, Sherrod Brown, Debbie Mucarsel-Powell, and Colin Allred.

However, because of institutional Republican advantages inherent to the nature of the Senate, a Democratic Senate is unlikely. The most likely outcome is a 49–51 or 48–52 Republican Senate. Donating to House races should be the priority, as there is a real chance that Democrats can flip that chamber.