If Vote Was Today, Immigration Reform Would Fail House

PHOTO: Tom Wong works in his favorite coffee shop in San Diegos North Park neighborhood.

SAN DIEGO — In 2012, statistician Nate Silver made headlines when he accurately predicted the outcomes for the presidential election in all 50 states.

While political scientists have been forecasting election results for decades, very few forecast legislation. But in San Diego, one assistant professor is doing just that. He’s forecasting the outcome for immigration reform.

Most days, you can find Tom Wong inside a boutique coffee shop in San Diego’s North Park neighborhood, hunched over a Macbook Pro.

The assistant professor of political science at UC San Diego is crunching thousands of numbers.

“I’m predicting opposition and support for immigration reform among all 535 current members of congress," Wong said.

How Does It Work?

His forecast is created in three steps. The first is a model that determines what factors create a 'yes' or 'no' vote on immigration.

It begins in 2006. That was the year millions of immigration advocates protested in the streets across the United States, rallying against H.R. 4437, an enforcement-heavy immigration bill.

Many cite these demonstrations as the starting point for the modern immigration movement.

In step one, Wong counts every vote cast by every member of Congress on immigration since 2006. Then he pulls a ton of data — unemployment rates, education levels, ethnic makeup — from states and districts.

Wong explains his model is taking into account "the factors that previous research has identified as being important for immigration policy."

He uses that information to create a model that predicts how a member of Congress will vote based on what their state or district looks like.

Step two is seeing if his model is accurate.

Wong looks at each member of Congress since 2006 to see whether his model accurately predicted how they actually voted on immigration bills.

"In the House we’re talking about a 94 percent match rate. And the Senate we get about 90 percent," said Wong.

Step three is using the model as a predictor. For example, how will freshmen members of Congress vote, someone like Sen. Ted Cruz (R-Texas)?

"His state has certain demographic characteristics, certain economic characteristics and he’s a Republican," explains Wong.

It shouldn’t be a surprise that the model predicts Cruz will be voting against the bill. But what about the rest of the Senate and members of the House?

"Right now the data points to 67 to 71 'yes' votes in the Senate. For the House we’re only seeing about 203 'yes' votes," Wong said.

So if voted on today, according to Wong's model, the Senate’s comprehensive immigration reform bill would fail by 15 votes in the House.

But, Wong wants immigration reform to pass.

Seeking Change

"My own immigration experience gives me this window into the data where the results are more than just numbers, because I see the families and the people that can potentially benefit," he said.

When Wong was 16 years old he learned that he and his family had overstayed their tourist visas from Hong Kong. They were living here illegally.

Although they have since become legal residents, that moment is always with him.

"It is very easy for me to simply close my eyes and feel exactly how I felt as my 16-year-old self," Wong said.

It’s a feeling that he believes is shared among many of the young immigrants who are rapidly changing the demographics of districts across the United States.

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