States Don't Have to Implement ObamaCare Exchanges

Many states including Florida, Ohio, Wisconsin, and Maine say they will not implement ObamaCare in their states. One thing these states have in common is that they are run by Republican governors. And of course this has liberals angry since they insist these states must implement the legislation because it is the law of the land and the Supreme Court deemed the law constitutional.

It is true the Supreme Court found Obamacare constitutional including the controversial mandate. They said the mandate was a “tax” and therefore did not violate the commerce clause. The court also concluded that the federal government could not withhold Medicaid funding from states that decide not to implement the law. In other words, the federal government could not use any form of coercion to force states to implement the ObamaCare.

I am a true believer in state’s rights and feel strongly states should implement laws that their citizens want, not the laws the federal government thinks they should implement. Case in point, Colorado recently amended their Constitution to legalize marijuana and to limit campaign contributions. I voted against both of these constitutional amendments, but if this is the will of the people then so be it. To further complicate matters both of these amendments violate federal law. Federal law prohibits the possession and use of marijuana for recreational purposes and the Supreme Court ruled in favor of Citizens United which says campaign contributions should not be capped. I like it when states fight back and implement the will of the people even if I do not like the law. States know better how to govern its citizens than the federal government. After all, Colorado is uniquely different from New Jersey or Alabama.

Immigration is a good example of federal government bias. Why can’t states like Arizona implement immigration laws that better protect their citizens? The Department of Justice (DOJ) intervened against Arizona because they did not like the law’s ideology, not its position with federal law. After all, the DOJ did not interfere with San Francisco’s policy as being a “sanctuary” city for illegal immigrants. San Francisco is not adhering to federal law, but most citizens in San Francisco do not want the city to enforce the federal laws for illegal immigration which includes deportation. If San Francisco is allowed to violate federal law on illegal immigration then Arizona should be allowed to enforce its illegal immigration laws. Our administration is picking policy fights based on ideology, not based on enforcing the federal law equally.

Elections are another great example. The Supreme Court should have never ruled on the 2000 election. The federal government has absolutely no jurisdiction over state elections and election laws. If states decide to purge their voter data bases omitting ineligible voters and want to implement stricter voter ID laws then so be it. Liberals argue that these are efforts to suppress minority vote. This is far from the truth and the 2012 election is a prime example. Minorities made up a record 28% of the electorate. Minority turn out far exceeded population growth over the past four years while the White vote was down 8% (adjusted for population growth). In fact, most states have initiated very liberal early voting policies making easier for anyone to vote in elections. In the face of dozens of new election laws in a dozen states minority turnout increased – that is a fact. So let the states decide their election laws.

Laws should be the will of the states, not the will of federal liberal or conservative ideologies. If Obama’s DOJ sees fit to exempt Colorado from federal marijuana and campaign finance laws then they should be consistent and let states implement their healthcare, immigration, and election laws even if they do not comply with federal law. However, in the case of ObamaCare the Supreme Court ruled the U.S. government could not use coercion to force states to implement the law.

Lessons Learned About Election Polls

Throughout the 2012 presidential election process both Republicans and Democrats cried foul over election polls. The most common complaint – the poll was either over-sampling or under-sampling political ideology. This complaint was mostly heard from the conservative side since they were regularly down in both national and battleground state polls. Occasionally, we would hear someone complain about a poll’s demographic makeup, but it was rare. In a few instances, the Democrats complained that some polls underestimated the minority turn out – and they were right.

Truth be told, the hardest thing for election polls to model is political ideology. Political ideology changes routinely amongst some people. However, a person’s demographics never change! For this reason, most polling companies do not consider the political ideology of the electorate when conducting polls (most polls provide the data for political ideology makeup of the poll participants, but they do not use this information to model actual results). Instead, polling companies focus solely on the demographics – they want the demographics of the poll sample to resemble the electorate demographics (national or on the state level). Thus, they make sure that gender, ethnicity, age, and other demographics in the poll resemble the electorate. Once the poll is complete, the pollsters let the political ideology fall as it may.

In 2008, an independent or unaffiliated voter may consider their political ideology as lean Democratic or Democrat if they voted for Obama. However, that same person in the 2012 election may consider their political ideology as lean Republican or Republican if they voted for Romney. For this reason political ideology is hard to sample. However, the same person’s age, gender, and ethnicity are not going change (age changes, but it will be the same during the calendar year of the election). To make modeling political ideology more troubling is many states do not track party affiliation. And states that track political ideology data, a person may change their political affiliation to vote in a primary and not change it back before Election Day. For example, a liberal may change their affiliation to vote in the 2012 Republican primary. After all, most liberals already knew that Obama was going to win the Democratic nomination. For these reasons, it is much more accurate for polling companies to focus on the demographic makeup of the electorate.

The average of 17 national polls had Obama winning by 0.7% while the political ideology of the electorate favored Democrats by 5.2%. In the end, Obama won the election by nearly 3% and the political ideology of the electorate favored Democrats by 6%. Using the same data I predicted the outcome of the election using 3 methods. I modeled the political ideology makeup of the electorate to favor Democrats by 4%. Under this model Romney held a slight lead in the popular vote. However, if I modeled the election based on the demographic makeup of the electorate at 53% (women) - 47% (men), and 75% (white) - 25% (non-white), Obama won using both models in a fairly close election. In the end, the actual ethnicity makeup was 72% (white) – 28% (non-white) and obviously Obama won easily with that demographic makeup of the electorate. Hence, while modeling the national election poll data, I was able to correctly predict the outcome of the election using demographics (even though I still did not predict the ethnicity makeup of the electorate correctly), but was wrong when I used political ideology.

Therefore, in the future, pollsters and people critiquing polls would be more accurate and prudent to concentrate on the demographic makeup and not political ideology of the poll participants. Still, it is difficult to predict the outcomes of elections because pollsters must predict if the youth vote will show up, will the minority vote show up, will single women show up, and so forth. For example, in 2004, exit polls showed that John Kerry was going to win easily over George Bush. However, the exit polls consisted of a gender makeup that was 57% women and only 43% male (this should have obviously been seen as a poor sample). Hence, when the actual gender makeup of the electorate was 53% women and 47% male, the exit polls were grossly wrong. Women tend to be more liberal than men.

The Real Reason We Face the Fiscal Cliff

There are many issues with Congress justifying why they have approval ratings in the low teens. To me, the most glaring issue is the professional background experience of Congressional leaders. Only five members of Congress have a background in math, science, and or engineering. And there are a total of 7 accountants. In all, there are 12 members out of 535 Representatives and Senators with a math or science background (just a little more than 2%). Congress is dominated by one profession – Lawyers. There are 222 Lawyers in the House and Senate (over 41%). And believe it or not this number is down from 277 lawyers forty years ago and 257 lawyers 30 years ago. And what’s worse, the executive branch is usually occupied by lawyers with limited math experience. In fact, Obama makes fun of his math skills which he rates at the 7^th grade level. Yet, this is the same president who said Romney’s budget math was wrong and his administration is responsible for setting graduating standards for high school level math.

What are the biggest problems facing our country today? They are complicated fiscal issues. Yet, year in and year out, the electorate reinstates over 90% of incumbents (most of whom are lawyers) who continue to push the country towards fiscal oblivion or the fiscal cliff. Our government has failed to pass a budget in nearly 4 years. Congress does not seem to understand or comprehend that if the U.S. had a balanced budget the country would operate more efficiently and consequently allow the economy to expand and grow. Simply put, this creates less uncertainty for business owners.

There is a need for lawyers, but for the most part the profession is overrated and there are too many of them in the United States. I blame too many lawyers for creating a society which is lawsuit happy and this is a big reason for inflation. For instance, one reason medical costs are soaring is because of frivolous lawsuits which subsequently cause the price of medical malpractice insurance to skyrocket. Frivolous lawsuits against any company will drive up the cost for goods and services. In fact, lobbying for businesses, groups, and organizations is big Washington DC business and is made up of thousands of lawyers who carve special deals for their clients and simply put, complicate legislation. This is why ObamaCare is over 2000 pages long and why our tax code is over 4 million words – lawyers make legislation convoluted, ambiguous, and abstract. It is no surprise that tort reform of any kind is never brought up in Congress.

We have a branch of government that is chartered with upholding the law of bills and legislation – the Supreme Court. So why then do we need hundreds of more lawyers in other branches of government? The law is abstract and ambiguous and therefore, each person can have a unique interpretation of the constitution – and there are no right answers (although we all think we know the right answer). Whereas, math and engineering solutions are exact – there are right answers. Engineers are technical writers which is a more direct, easy to understand, and a less convoluted way to write legislation then laws written by lawyers filled with confusing jargon open to multiple interpretations and hence, different implementations of the law. Good engineers can explain solutions to complicated issues in terms the common man can understand.

In 2011, the government granted 85,000 H1-B visas (equivalent to 1 month of job growth under Obama) to foreigners to do for the most part engineering, math, and science jobs. Yes, Americans trained to do technical jobs is a dying breed in the United States. These are high paying jobs and these jobs are the ones that generate the most proprietary information and patents. The people doing these jobs are the inventors and innovators which are necessary to create new business ideas and products that will keep the U.S. a global economic leader. Foreigners get educated at our universities, get trained at our companies, and then go home to create a business to compete against U.S. companies. This is why America and the U.S. economy are losing ground to China and other countries around the globe. We need math and science professionals in Washington to correct this glaring problem. Lawyers do not understand this problem – in fact their solution to the problem is to generate more H1-B visas instead of correcting our educational flaws.

The Art of Being Unaccountable

I have witnessed carbon emitting oxygen thieves throughout my corporate days. These are the unaccountable people who are able to survive year in and year out. Not only are unaccountable people becoming more common in the workplace, these people are being put into managerial roles. The same is happening in politics. And no one is more unaccountable for his actions than our President. He has gotten it down to an art form and below is his manifesto to being unaccountable:

• Do not answer tough questions. In other words, avoid press conferences and interviews with media outlets.
• Never do anything that is not scripted. All the president’s words must be read off a teleprompter.
• Go on talk shows and yuck it up with people who support your point of view. This will enhance your personal image.
• Leak beneficial information such as the details on the killing of Osama Bin Laden and cyber warfare technology that is being used against Iran.
• Cover up information and hide behind executive privilege on things that are not beneficial such as Libya and Fast and Furious.
• When something is unpopular such as Obamacare and the Recovery Act, do not talk about it.
• Make up statistics, such as “jobs saved”, to make your policies, such as the Recovery Act, look as if they are working.
• Make sure to get media outlets and reporters complicit with your ideas and agenda.
• When you are becoming unpopular reach out to people who are suffering and uneducated with free handouts and entitlements.
• Avoid being seen around negative images such as Hurricane Sandy or the BP oil spill.
• Blame others for things that are going wrong, such as Bush for the stagnant economy.
• Take credit for things that are going well such as the auto bailout, TARP, and Iraq – all policies started under Bush.
• Avoid passing a budget.
• Use political correctness to make actions sound more appealing such as calling terrorism a manmade disaster.
• Attack your adversaries personally and make them look evil (Hillary, Mitt, Republican Congress).
• Appoint a knucklehead as your VP so you always look good.
• Deny any prior knowledge to any potential cover up or fraudulent stories such as Fast Furious, Libya, and Petreaus sex scandal.
• Surround yourself with more people to be accountable for your mistakes such as the appointment of Czars who receive no congressional oversight.
• Lie or stretch the truth if it is beneficial.
• Deflect unfavorable stories. For instance, turn Hurricane Sandy into a climate change story.
• Never let a good crisis go to waste. For instance, turn the BP oil spill into a story about renewable energies.
• Create diversions such as the Petreaus sex scandal or the anti-Muslim film to cover up the truth behind unfavorable events such as the Libya attack.
• Avoid transparency and the freedom of information act.

Four More Years of This!

The next four years will be difficult and I predict domestic and foreign issues will continue to digress. If the first two weeks since Obama has been reelected is any indication of things to come, we are all facing difficult times ahead.

Europe has officially slid into its second recession of the Obama Presidency. Eurozone unemployment is at 11.1% and the Euro still faces a collapse with Greece, Ireland, Spain, and Portugal debt at massive levels. What is happening in Europe does not bode well for the United States. In the first week after the Obama reelection unemployment filings went up nearly 25% (78 thousand). Why? These layoffs are coming because companies know Obama is set to increase taxes on businesses and they know ObamaCare and its taxes will go into effect in 2014. Personally, I have insight into the semiconductor industry and know that the manufacturing facilities are only half loaded. Semiconductors are used to make all electronic products. Therefore, this is a good indication that the economy is slowing and it is no surprise the semiconductor industry has already announced layoffs.

The situation in the Middle East continues to deteriorate. The Arab spring was a nightmare. Egypt is no longer a reliable ally. Libya is so unstable that all Western countries have removed their embassies. Syria is in a bloody civil war. Israel and Palestinian Hamas are at war. Syria is at war with Turkey. The U.S.-Pakistan relationship is teetering on failure. Afghanistan remains unstable despite Obama’s escalation of the war. Iran is getting closer to a nuclear bomb. And the U.S. has been recently attacked by Egypt (Embassy), Libya (Embassy), and Iran (Drone in neutral airspace). The bottom line is that U.S. – Middle East relations are deteriorating at an alarming pace.

The administration is claiming ignorance (that it was unaware) on the deteriorating security in Libya that led to the embassy attack and subsequent death of 4 Americans. The administration is also claiming ignorance over the fact the CIA chief was compromised and confidential files were removed from his watch. Instead, the administration chose to lie and deceive the American public over what happened in Libya so Obama could win reelection. What’s worse, the media was complicit with this cover up.

The Labor Department reports that people living in poverty spiked to its highest levels in October, 16% (over 50 million Americans). This is good news for Democrats who depend on this electorate who vote liberally because they like the entitlements poverty brings them. However, how long can these handouts last before austerity measures are needed?

Health insurance premiums went up on average by 15% this past year and they have gone up over 40% since ObamaCare was passed. Even though the legislation will not go into law until 2014 companies must prepare for its high cost. The Affordable Care Act is the most deceiving name this law can have.

In the face of the fiscal cliff, Democrats still insist the best way to handle our 16 trillion dollar debt is to raise taxes on the wealthy, avoid cutting spending (except military), and refuse any entitlement reform.

2012 Election Polls and Models (Actual)

Time to see how the model held up.

Below are poll averages (from Real Clear Politics) for Presidential, Gubernatorial, Senate, and contested House seats. A positive poll average favors the Republican candidate whereas a negative poll average favors the Democratic candidate. From the poll averages a ranking and probability are calculated for each race. A probability above 0.5 (50%) favors the Republican candidate whereas a probability under 0.5 favors the Democratic candidate. The higher ranking, the higher the probability the race will go to the Republican candidate. The lower the ranking, the higher the probability the race will go to the Democratic candidate. Since polling in House races are not very accurate, the formula to calculate the probability is more complex taking into account race ratings by the Cook, Election Projection, and Sabato political reports as well as generic congressional polling results and PVI (Partisan Voting Index). A positive PVI means the percentage of registered Republicans in the district outnumbers registered Democrats whereas a negative PVI means the percentage of registered Democrats in the district outnumbers registered Republicans. The overall probability for the President, Senate, Gubernatorial, and House races are computed to project the number of seats (including the presidency) that are going to be won by Republicans and Democrats respectively. Race candidates will be filled in to the below tables once they are determined by state primaries. I will update and post this information regularly. Below is an overall summary of the predicted outcomes based on probability density function models.

Presidential Electoral Vote Projection: Obama 277; Romney 261 (R +88), Obama at 51.5% of winning the election.

Actual: Obama 323; Romney 206 (R +33)

Governor Races: Current - Republicans 29; Democrats 19 (2 Independents); Projection - Republicans 32; Democrats 18 (including 2 Independents)

Actual: Republicans 30; Democrats 18 (Including 2 Independents)

Senate Races: Current - Republicans 47; Democrats 53 (Including 2 Independents); Projection - Republicans 50; Democrats 50 (Including 2 Independents)

Actual: Republicans 45; Democrats 55 (Including 2 Independents)

House Races: Current - Republicans 242; Democrats 196; Projection: Republicans 240; Democrats 198;

Actual: Democrats 201; Republicans 234

Popular Vote Projection: 48.9% Romney – 48.8% Obama – 2.3% other candidates

Actual: Romney 48%; Obama 51%

Below is an overall summary of the predicted outcomes based solely on election polls:

Presidential Electoral Vote: Obama 303; Republican 235

Governor Races: Republicans 30; Democrats 20 (including 2 Independents)

Senate Races: Republicans 48; Democrats 52 (Including 2 Independents)

House Races: Republicans 238; Democrats 200

Races Highlighted below where the incorrectly picked races and results. The model picked one Presidential state wrong (Florida), one governor race (Montana), 2 Senate Races wrong (Montana and Indiana), and 14 House races wrong. What was disappointing about the House projections is that 9 of those races had near a 2 to 1 probability of going the other way. It may be time to tweak the House model.

		Presidential Race
State	Democrat Electoral Vote	Republican Electoral Vote	Poll	Rank	Probability	Weighted Probability
Alabama		9	19	10	0.8106639	5.674647377
Alaska		3	25	6	0.8766392	0.876639245
Arizona		11	7.5	23	0.6358939	5.723045483
Arkansas		6	27	4	0.8945359	3.578143647
California	55		-14	42	0.258274	13.68852371
Colorado	9	0	-1.5	27	0.4722954	3.306068041
Connecticut	7		-10.8	38	0.3083943	1.541971475
Delaware	3		-20	44	0.1770465	0.177046493
DC	3		-75	51	0.0002554	0.000255381
Florida	0	29	1.5	25	0.5277	14.2480233
Georgia		16	12.3	17	0.7156299	10.01881868
Hawaii	4		-28	49	0.0972552	0.19451036
Idaho		4	38	3	0.9608546	1.921709279
Illinois	20		-15	43	0.2435246	4.383443596
Indiana		11	9.5	20	0.670094	6.030846004
Iowa	6		-2.4	29	0.4557283	1.822913069
Kansas		6	20	8	0.8229535	3.29181403
Kentucky		8	15	16	0.7564754	4.538852135
Louisiana		8	18	11	0.7978628	4.787176513
Massachusetts	11		-20	44	0.1770465	1.593418433
Maine	4		-11.5	39	0.2970719	0.594143865
Maryland	10		-20.7	46	0.1687509	1.350006802
Michigan	16		-3.8	32	0.4301198	6.021677608
Minnesota	10		-5.2	35	0.4048021	3.238416835
Mississippi		6	20	8	0.8229535	3.29181403
Missouri		10	11.6	19	0.7045299	5.636239281
Montana		3	9	21	0.6616629	0.661662902
Nebraska		5	16	14	0.7707574	2.312272273
Nevada	6		-2.8	30	0.448388	1.793551984
New Hampshire	4	0	-2	28	0.4630837	0.926167363
New Jersey	14		-11.8	40	0.2922784	3.507340582
New Mexico	5		-9.3	37	0.3332684	0.999805137
New York	29		-26.4	48	0.1106239	2.98684515
North Carolina	0	15	3	24	0.5552757	7.218583888
North Dakota		3	17.7	12	0.7939237	0.793923676
Ohio	18		-3	31	0.4447243	7.115589061
Oklahoma		7	27	4	0.8945359	4.472679559
Oregon	7		-6	36	0.3905047	1.952523531
Pennsylvania	20		-3.8	32	0.4301198	7.742156925
Rhode Island	4		-23	47	0.1432838	0.286567698
South Carolina		9	12	18	0.7108972	4.976280374
South Dakota		3	8.5	22	0.65315	0.653149961
Tennessee		11	25	6	0.8766392	7.889753205
Texas		38	17	13	0.7845573	28.24406378
Utah		6	52	1	0.9920099	3.968039526
Vermont	3		-37	50	0.0432316	0.04323159
Virginia	13	0	-0.3	26	0.4944548	5.439002847
Washington	12		-13.6	41	0.2643008	2.643008306
West Virginia		5	16	14	0.7707574	2.312272273
Wisconsin	10		-4.2	34	0.422852	3.382815999
Wyoming		3	40	2	0.9680845	0.968084534
			0
Total	303	235	21.5824		0.5333475	0.484642613	0.43841526	0.486
Governor Races
State	Democrat	Republican	Poll	Rank	Probability			Incumbent
Delaware	Markell	Cragg	0	6	0.5				-1
Indiana	Gregg	Pence	11	4	0.6798829				1
Missouri	Nixon	Spence	-10.3	9	0.3308274				-1
Montana	Bullock	Hill	1.5	5	0.52541	Gain	1		-1
New Hampshire	Hassan	Lamontagne	-3.6	8	0.4392157				-1
North Carolina	Dalton	McCrory	15.7	3	0.7476351	Gain	1		-1
North Dakota	Taylor	Dalrymple	28	2	0.8829124				1
Utah	Cooke	Herbert	53	1	0.9878351				1
Vermont	Shumlin	Brock	-34	11	0.0742848				-1
Washington	McKena	Inslee	-1	7	0.4830547				-1
West Virginia	Tomblin	Maloney	-21	10	0.1861283				-1
			0
			23.5359		0.5306532		2
Senate Races
State	Democrat	Republican	Poll	Rank	Probability			Incumbent
Arizona	Carmona	Flake	4	7	0.5793408			1
California	Feinstein	Emken	-20.6	26	0.1512545			-1
Connecticut	Murphy	McMahon	-5	17	0.4011935			-1
Delaware	Carper	Wade	-25	27	0.1054133			-1
Florida	Nelson	Mack	-6.9	20	0.3649128			-1
Hawaii	Hirono	Lingle	-17	23	0.1974177			-1
Indiana	Donnelly	Mourdock	1	9	0.51996			1
Massachusetts	Warren	Brown	-3.5	15	0.4304685	Gain	-1	1
Maine	Dill	Summers	0	12	0.5	Gain	0	1
Michigan	Stabenow	Hoekstra	-13.2	22	0.2544074			-1
Minnesota	Klobuchar	Bills	-31	30	0.0603782			-1
Mississippi	Gore	Wicker	20	4	0.8415955			1
Missouri	McCaskill	Akin	-4.5	18	0.4108989			-1
Maryland	Cardin	Bongino	-28.5	28	0.0768653			-1
Montana	Tester	Rehberg	0.4	10	0.50799	Gain	1	-1
Nebraska	Kerrey	Ficsher	17	5	0.8025823	Gain	1	-1
Nevada	Berkley	Heller	3.5	4.8	0.5695315			1
New York	Gillibrand	Long	-41.4	33	0.0191259			-1
New Jersey	Menendez	Kyrillos	-17.4	24	0.1919039			-1
New Mexico	Heinrich	Wilson	-10.7	21	0.2961332			-1
North Dakota	Heitkamp	Berg	5.7	6	0.6122911			-1
Ohio	Brown	Mandel	-5.3	18	0.3953989			-1
Pennsylvania	Casey	Smith	-5.4	19	0.3934725			-1
Rhode Island	Whitehouse	Hinkley	-26	28	0.0965697			-1
Tennessee	Clayton	Corker	38	2	0.9714124			1
Texas	Sadler	Cruz	22	3	0.8645822			1
Utah	Howell	Hatch	41	1	0.9799213			1
Vermont	Sanders	MacGovern	-40	32	0.0226384			-1
Virginia	Kaine	Allen	-1.7	13	0.4660957			-1
Washington	Cantwell	Baumgartner	-19	25	0.170806			-1
West Virginia	Manchin	Raese	-39	31	0.0254678			-1
Wisconsin	Baldwin	Thompson	-2.2	14	0.4561595			-1
Wyoming	Chesnut	Barrasso	1	9	0.5199595			1
			0
			19.9793		0.4017013		1
House Races
State	Democrat	Republican	Poll	PVI	Cook	Sabato	Election Projection	AVE	Rank	Probability				Incumbent
Arkansas 1	Ellington	Crawford	25	7	15	15	15	12.9	2	0.9579113				1
Arkansas 2	Rule	Griffin	0	5	15	15	15	10	14	0.9096687				1
Arkansas 4	Jeffress	Cotton	29	8	15	15	15	13.5	1	0.9646398	Gain	1		-1
Arizona 1	Kirkpatrick	Paton	1	3	0	-5	-5	-1.3	84	0.4309196	Gain	-1		1
Arizona 5	Morgan	Salmon	0	5	15	15	15	10	14	0.9096687				1
Arizona 2	Barber	McSally	-6.1	3	-10	-10	-10	-6.01	104	0.2105341				-1
Arizona 9	Sinema	Parker	-2.5	0	-5	-5	-5	-3.25	92	0.331751	Gain	-1		-1
California 3	Garamendi	Vann	-15	-1	-10	-15	-10	-8.7	115	0.1220733				-1
California 7	Bera	Lungren	5	3	0	-5	5	1.1	75	0.55854				1
California 9	McNerney	Gill	-9	-2	-5	-5	-5	-4.3	97	0.2824263				-1
California 10	Hernandez	Denham	4.5	5	0	-5	10	2.45	73	0.6285388				1
California 16	Costa	Whelan	0	-2	-15	-15	-15	-9.4	120	0.1041245				-1
California 21	Hernandez	Valadao	4	3	10	10	10	7	48	0.8256471	Gain	1		1
California 23	Phillips	McCarthy	0	18	15	15	15	12.6	3	0.9541776				1
California 24	Capps	Maldonado	1	-3	-5	-5	5	-1.5	85	0.4204245				-1
California 26	Brownley	Strickland	0	-3	0	-5	-5	-2.6	89	0.3638951	Gain	-1		-1
California 31	Dutton	Miller	0	-2	15	15	15	8.6	36	0.8751951				1
California 36	Ruiz	Bono Mack	3	3	0	5	5	2.9	67	0.65108				1
California 41	Takano	Tavaglione	-4	-3	-5	-5	-5	-4	94	0.2961565	Gain	-1		1
California 47	Lowenthal	DeLong	0	-5	-10	-10	-10	-7	107	0.1743529	Gain	-1		-1
California 52	Peters	Bilbray	1.5	-1	0	-5	5	-0.05	78	0.4973297	Gain	-1		1
Colorado 3	Pace	Tipton	11	4	5	5	5	4.9	55	0.7440789				1
Colorado 4	Shaffer	Gardner	0	6	15	15	15	10.2	10	0.9139508				1
Colorado 6	Miklosi	Coffman	3	1	0	5	5	2.5	73	0.6310666				1
Connecticut 5	Esty	Roraback	-5	2.5	-5	-5	-5	-3	91	0.3439836				-1
Florida 2	Lawson	Southerland	-1	4	5	10	10	5.7	53	0.7772889				1
Florida 9	Grayson	Long	-13	-3	0	-15	-15	-7.9	111	0.1451218	Gain	-1		-1
Florida 26	Garcia	Rivera	3	4	-5	-5	-5	-1.9	86	0.3996101	Gain	-1		-1
Florida 10	Demings	Webster	6	7	5	5	15	7	48	0.8256471				1
Florida 13	Ehrlich	Young	9	1	15	15	15	10.1	13	0.9118292				1
Florida 16	Fitzgerald	Buchanan	17	5	10	10	10	8.7	35	0.8779267				1
Florida 18	Murphy	West	4	1	0	5	5	2.6	71	0.6361				1
Florida 7	Kendall	Mica	0	4	15	15	15	9.8	19	0.9052304				1
Florida 22	Frankel	Hasner	-6	-5	-10	-5	-5	-5.6	101	0.2267231	Gain	-1		1
Georgia 12	Barrow	Anderson	-4	10	0	5	5	3.6	61	0.68508	Gain	1		-1
Illinois 8	Duckworth	Walsh	-12	-5	-10	-5	-10	-7.2	109	0.1675538	Gain	-1		1
Illinois 10	Schneider	Dold	5	-8	-5	-5	5	-2.1	88	0.389305	Gain	-1		1
Illinois 11	Foster	Biggert	-1	-6	-5	-5	-5	-4.3	97	0.2824263	Gain	-1		1
Illinois 12	Enyart	Plummer	-3	-2	0	5	-5	-0.7	80	0.4626697				-1
Illinois 13	Gill	Davis	-2	-1	0	-5	5	-0.4	79	0.47865	Gain	-1		1
Illinois 17	Bustos	Schilling	3	-6	0	-5	-5	-2.9	90	0.3489236	Gain	-1		1
Indiana 2	Mullen	Walorski	0	7	10	10	10	7.4	45	0.8390721	Gain	1		-1
Indiana 8	Crooks	Bucshon	0	7	5	5	10	5.4	54	0.7651317				1
Iowa 1	Braley	Lange	0	-5	-10	-10	-15	-8	112	0.1420905				-1
Iowa 2	Loebsack	Archer	0	-4	-10	-5	-15	-6.8	106	0.1813247				-1
Iowa 3	Boswell	Latham	0	1	5	5	5	3.2	64	0.6658163	Gain	1		-1
Iowa 4	Vilsack	King	4	4	5	5	5	4.2	57	0.7130311				1
Kentucky 6	Chandler	Barr	-5	9	0	-5	-5	-0.7	80	0.46267				-1
Maine 2	Michaud	Raye	-15.5	-3	-15	-15	-15	-11.2	133	0.0677617				-1
Maryland 1	Rosen	Harris	0	10	15	15	15	11	5	0.9295692				1
Maryland 6	Delany	Bartlett	-1	-2	-10	-10	-10	-6.5	105	0.1921047	Gain	-1		1
Massachusetts 9	Keating	Sheldon	0	-5	-15	-15	-15	-10	126	0.0903313				-1
Massachusetts 6	Tierney	Tisei	7.5	-7	5	5	10	3.4	63	0.67309	Gain	1		-1
Missouri 2	Koenen	Wagner	0	5	15	15	15	10	14	0.9096687				1
Michigan 1	McDowell	Benishek	-6	3	0	-5	-5	-2	87	0.39445	Gain	-1		1
Michigan 3	Pestka	Amash	9	6	10	5	15	8.1	40	0.8608977				1
Michigan 7	Haskell	Walberg	0	1	15	15	15	9.2	27	0.8909546				1
Michigan 11	Taj	Bentivolio	8	1	10	10	10	7	48	0.8256471				1
Minnesota 1	Walz	Quist	0	1	-15	-15	-15	-8.8	116	0.119384				-1
Minnesota 2	Obermueller	Kline	8	1	10	10	15	8	42	0.8579095				1
Minnesota 3	Barnes	Paulsen	0	0	15	15	15	9	31	0.8858687				1
Minnesota 6	Graves	Bachman	5.5	8	5	10	15	8.15	39	0.8623757				1
Minnesota 8	Nolan	Cravaack	-2	-3	0	-5	5	-0.8	82	0.4573558	Gain	-1		1
Minnesota 7	Peterson	Byberg	0	5	-15	-15	-15	-8	112	0.1420905				-1
Montana 1	Gillan	Daines	7	7	10	10	10	8.1	40	0.8608977				1
New Jersey 3	Adler	Runyan	13.5	2	5	10	10	6.75	51	0.8169054				1
New Jersey 5	Gussen	Garrett	0	7	15	15	15	10.4	9	0.9180792				1
New Jersey 6	Pallone	Little	0	-8	-15	-15	-15	-10.6	131	0.0779435				-1
New Jersey 7	Chivukula	Lance	0	3	15	15	15	9.6	21	0.9006334				1
New Jersey 8	Sires	Karczewski	0	-10	-15	-15	-15	-11	132	0.0704308				-1
New York 2	Falcone	King	0	-1	15	15	15	8.8	33	0.880616				1
New York 3	Israel	Labate	0	-5	-15	-15	-15	-10	126	0.0903313				-1
New York 1	Bishop	Altschuler	-6	0	-5	-5	-5	-3.6	93	0.3149248				-1
New York 4	McCarthy	Becker	0	-3	-15	-15	-15	-9.6	122	0.0993666				-1
New York 11	Murphy	Grimm	14	5	5	10	10	7.4	45	0.8390721				1
New York 18	Maloney	Hayworth	5	2	0	5	5	2.9	67	0.65108				1
New York 19	Schreiban	Gibson	9	-1	0	5	5	2.7	70	0.6411199				1
New York 22	Lamb	Hanna	0	3	15	15	15	9.6	21	0.9006334				1
New York 21	Owens	Doheny	-8	1	-10	-5	-10	-5.6	101	0.2267231				-1
New York 24	Maffei	Buerkle	-3	-4	-5	-5	-5	-4.1	95	0.2915458	Gain	-1		1
New York 25	Slaughter	Brooks	-11	-5	-10	-5	-10	-7.1	108	0.1709317				1
New York 23	Shinagawa	Reed	5	3	15	10	15	9.1	30	0.8884323				1
New York 27	Hochul	Collins	3	7	0	5	5	3.7	60	0.6898149	Gain	1		-1
Nebraska 2	Ewing	Terry	9	6	15	15	15	11.1	4	0.9313574				1
New Hampshire 1	Shea-Porter	Guinta	2	0	5	5	5	3.2	64	0.66582				1
New Hampshire 2	Kuster	Bass	-6	-3	-5	-5	-5	-4.2	96	0.2869689	Gain	-1		1
New Mexico 1	Grisham	Arnold-Jones	-14	-5	-15	-15	-15	-11.4	134	0.0634877				-1
Nevada 2	Koepnick	Amodei	0	5	15	15	15	10	14	0.9096687				1
Nevada 3	Oceguera	Heck	9	0	0	5	5	2.9	67	0.6510764				1
Nevada 4	Horsford	Tarkkanian	9	-2	0	-5	5	0.5	77	0.5266836				-1
North Carolina 2	Wilkins	Ellmers	16	2	15	15	15	11	5	0.9295692				1
North Carolina 7	McIntyre	Rouzer	11	11	0	-5	-5	1.3	74	0.56908	Gain	1		-1
North Carolina 8	Kissell	Hudson	2	12	10	10	10	8.6	36	0.8751951	Gain	1		-1
North Carolina 11	Rogers	Meadows	0	13	10	10	10	8.6	36	0.8751951	Gain	1		-1
North Carolina 13	Malone	Holding	0	10	10	15	15	10	14	0.9096687	Gain	1		-1
North Dakota 1	Gullleson	Cramer	7.5	10	10	10	15	9.75	20	0.9040961				1
Ohio 6	Wilson	Johnson	1	5	5	5	5	4.1	58	0.7084542				1
Ohio 7	Healey-Abrams	Gibbs	0	4	10	15	10	7.8	44	0.8518036				1
Ohio 16	Sutton	Renacci	-2	4	0	-5	5	0.6	76	0.5320098				1
Oklahoma 2	Wallace	Mullin	12	14	10	5	10	9	31	0.8858687	Gain	1		-1
Oregon 1	Bonamici	Morgan	0	-5	-15	-15	-15	-10	126	0.0903313				-1
Oregon 5	Schrader	Thompson	0	0	-15	-15	-15	-9	117	0.1141313				-1
Pennsylvania 3	Eaton	Kelly	0	3	15	15	15	9.6	21	0.9006334				1
Pennsylvania 4	Perkinson	Perry	19.5	6	-15	-15	-15	-5.85	103	0.2167695				-1
Pennsylvania 6	Trivedi	Gerlach	24	1	10	10	15	9.6	21	0.9006334				1
Pennsylvania 7	Badey	Meehan	0	1	15	15	15	9.2	27	0.8909546				1
Pennsylvania 8	Boockvar	Fitzpatrick	2	-1	5	10	5	4	59	0.7038435				1
Pennsylvania 12	Critz	Rothfus	-4	6	0	-5	-5	-1.2	83	0.43619				-1
Pennsylvania 11	Stilp	Barletta	0	6	15	15	15	10.2	10	0.9139508				1
Pennsylvania 15	Daugherty	Dent	0	2	15	15	15	9.4	26	0.8958755				1
Pennsylvania 18	Maggi	Murphy	0	6	15	15	15	10.2	10	0.9139508				1
Pennsylvania 17	Cartwright	Cummings	0	6	-15	-15	-15	-7.8	110	0.1481964				-1
South Carolina 7	Tinubu	Rice	0	6	10	15	15	9.2	27	0.8909546				1
South Dakota 1	Varilek	Noem	5	10	10	10	15	9.5	25	0.8982747				1
Tennessee 5	Cooper	Staats	0	-3	-15	-15	-15	-9.6	122	0.0993666				-1
Rhode Island 1	Cicilline	Doherty	2	-13	-5	-5	-5	-5.4	99	0.2348683				-1
Texas 10	Cadien	McCaul	0	8	15	15	15	10.6	8	0.9220565				1
Texas 14	Lampson	Weber	3	8	5	10	15	7.9	43	0.8548782				1
Texas 23	Gallego	Canseco	2.5	6	0	5	5	3.5	62	0.67791				1
Texas 34	Vela	Bradshaw	0	-3	-15	-15	-15	-9.6	122	0.0993666				1
Texas 35	Doggett	Narvaiz	0	0	-15	-15	-15	-9	117	0.1141313				-1
Utah 4	Matheson	Love	4	13	0	5	-5	3	66	0.65602	Gain	1		-1
Virginia 2	Hirschbiel	Rigell	13	5	10	10	5	7.3	47	0.8357808				-1
Virginia 11	Connolly	Perkins	0	-2	-15	-15	-15	-9.4	120	0.1041245				-1
Washington 1	Delbene	Kostar	1	-3	-5	-10	-10	-5.5	100	0.2307756				-1
Washington 6	Kilmer	Driscoll	-15	-5	-10	-15	-15	-10.5	130	0.0799135				-1
Washington 2	Larsen	Matthews	0	0	-15	-15	-15	-9	117	0.1141313				-1
Washington 3	Haugen	Buetler	0	-1	15	15	15	8.8	33	0.880616				1
Washington 10	Heck	Muri	0	-5	-15	-15	-15	-10	126	0.0903313				-1
West Virginia 1	Thorn	McKinley	0	9	15	15	15	10.8	7	0.9258855				1
West Virginia 3	Rahall	Snuffer	-28	6	-10	-10	-15	-8.6	114	0.1248049				-1
Wisconsin 3	Kind	Boland	0	-4	-15	-15	-15	-9.8	125	0.0947696				-1
Wisconsin 7	Kreitlow	Duffy	6	0	5	5	10	4.6	56	0.7309901				1
Wisconsin 8	Wall	Ribble	0	2	10	10	10	6.4	52	0.8042166				1