Impact of China's Retaliatory Tariffs on Democratic Vote Share Between 2016 and 2018
This research takes a look into the impacts of China's retaliatory tariffs on Democratic Vote Share between 2016 and 2018.
Link to the presentation: https://nbhabish-bbrpresentation.netlify.app/#1
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- [00:00:02.520]Hi there. I'm Bhabishya Neupane with
- [00:00:04.620]the Bureau of business research at
the University of Nebraska-Lincoln,
- [00:00:08.520]I'm a senior majoring in math
- [00:00:11.640]And the topic of my research for Nebraska
Research Day is impact of China's
- [00:00:16.200]retaliatory tariffs on democratic
vote share between 2016 and
- [00:00:21.330]2018. Motivation.
- [00:00:26.180]So the motivation behind this
project was two years back,
- [00:00:30.350]I was reading an article on
the US and China trade dispute.
- [00:00:34.190]The article talked about how China had
imposed tariffs on the US's agricultural
- [00:00:37.970]products, especially soybean.
- [00:00:40.760]And as soon as I was
done with the article,
- [00:00:43.130]I realized that China's retaliation
might have had some impact
- [00:00:46.610]in the midterm election of 2018,
- [00:00:49.100]given how the majority of soybean
producing States supported president
- [00:00:53.930]Trump in the presidential
election of 2016.
- [00:00:57.350]So this got me quite interested in
knowing if there was any impact and the
- [00:01:01.070]midterm election of 2018
- [00:01:05.870]Research question. The research
question for this project is
- [00:01:09.590]following China's retaliatory tariffs,
before the midterm election,
- [00:01:13.580]were soybean producing counties,
- [00:01:15.230]more likely to see shifts in the vote share
toward democratic candidates.
- [00:01:23.810]Method. To run our analysis
- [00:01:26.810]We decided to use ordinary
least square regression.
- [00:01:30.170]We have Change in democratic
vote share from 2016 to 2018
- [00:01:35.000]as our dependent variable. And
for our independent variables,
- [00:01:39.800]we have percent change in
soybean production from 2018 to
- [00:01:46.100]percent change in corn production
from 2018 to 2019 median household
- [00:01:50.990]income in 2018 unemployment rate in 2018
- [00:01:56.180]acres of soybean planted
in 2018 and Change in
- [00:02:00.620]Republican vote share from 2008 to 2010,
- [00:02:05.930]Data Sources. Collected data
are all County level data
- [00:02:11.120]Corn and soybean data came from the
United States department of agriculture
- [00:02:17.030]Election data for house of
representatives came from each state's,
- [00:02:20.810]secretary of state website,
- [00:02:24.020]the median household income and
unemployment rate data came from American
- [00:02:28.040]community survey and
Bureau of labor statistics.
- [00:02:37.310]Model. So this is what our model
looks like on the first model.
- [00:02:42.110]We haven't controlled for
historical voting patterns.
- [00:02:44.660]Whereas on the second model, we have
controlled for historical voting patterns.
- [00:02:49.370]I'll stay on the slide for a few seconds.
- [00:03:02.760]Results. Looking at our results.
- [00:03:05.100]We observe a statistically significant
negative coefficient for percent change in
- [00:03:10.020]soybean production from 2018
to 2019, in both of our models,
- [00:03:15.750]this implies that change in soybean
production from 2018 to 2019,
- [00:03:20.010]had an effect on the change in
democratic vote share. However,
- [00:03:24.030]when controlling for
historical voting patterns,
- [00:03:26.370]this effect was slightly reduced,
- [00:03:33.330]predicting change in democratic
votes share from 2016 to 2018.
- [00:03:39.060]So most of the counties that
produce soybean at high levels,
- [00:03:42.930]saw a decrease in the soybean production
in 2019 after the tariffs were imposed.
- [00:03:49.110]So to put things in perspective
- [00:03:52.260]We just observed a statistically
coefficient for percent change in
- [00:03:57.030]soybean production from 2018 to
2019 in the previous slide.
- [00:04:03.570]if we were to take a negative
percent change in soybean
- [00:04:08.490]from the table on the left and
plug it into the equation below,
- [00:04:13.320]we will observe a positive value since
negative beta coefficient is mulitplied
- [00:04:17.550]with a negative value and
like mentioned on the slide.
- [00:04:21.570]This means if there was a decrease
in soybean production from 2018 to 2019,
- [00:04:26.400]then we would observe a
positive association with
change in democratic votes share
- [00:04:30.750]from 2016 to 2018.
Talking about the limitations,
- [00:04:41.820]we had a couple of
limitations in our research,
- [00:04:45.060]missing production and data for many
counties in 2018 and 2019 limited,
- [00:04:50.040]the number of observations
in our analysis,
- [00:04:53.190]We also did a
- [00:04:54.810]and it showed that there were no
systematic differences between counties
- [00:04:58.110]with and without missing data. Also,
- [00:05:01.260]the difference in voter turnout from
Presidential to midterm elections were
- [00:05:05.400]not accounted for in
the model. And finally,
- [00:05:09.990]the model only contents
data from 4s out of 50 States
- [00:05:17.700]Conclusion. So to
conclude my presentation,
- [00:05:21.180]like we observed Changes in
soybean production from 2018 to
- [00:05:26.400]had an effect on the Change in
democratic vote share from 2016 to
- [00:05:31.260]2018. A decrease in soybean
production from 2018 to
- [00:05:35.580]2019 is associated with an increase
in democratic vote share. There,
- [00:05:40.740]this effect is slightly
reduced when historical
- [00:05:42.870]voting patterns are controlled
for. Historical voting patterns.
- [00:05:47.220]the controlled variable, is accounted
for by the Change in Republican
vote share from 2008
- [00:05:52.170]to 2010 in the model. Likewise, when
controlling for historical voting patterns,
- [00:05:57.740]the median household income was able
to explain some of the variance in the
- [00:06:01.430]dependent variable. Finally,
- [00:06:05.650]the model is able to explain very
little about the variance in Change in
- [00:06:09.790]democratic vote share from 2016 to 2018,
- [00:06:14.560]since the r-square is very.
- [00:06:18.640]Acknowledgements, I
want to take this time to,
- [00:06:21.340]thanks Dr. Herian and Dr. Jarrett
for helping me with this
- [00:06:25.870]project. And Thank you so much for
everyone who is watching this,
- [00:06:31.180]have a good one.
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