Friday, April 4, 2014

The Bitcoin Revolution

One of the hot topics in recent news is the emergence of a new medium of exchange called Bitcoin. Bitcoin is not legal tender (like the U.S. Dollar) which can be used to exchange for goods and services, but many people are hoping that it steps into that role within the coming years. So imagine that within the next decade you would no longer use Dollars for any, or at least the majority, of your transactions. Seems far-fetched right? Maybe not if you consider many other current events.

But before I cover the strong evidence for the possible Bitcoin revolution, lets examine what money is.
First, money is a medium of exchange. This is the basic premise of what we have all come to believe makes something money. We use money to get something. We also get money for doing something such as providing a good or service. But money is much more than that. Money has certain attributes which allow it to actually function as money.

  1. Money is Portable
  2. Money is Durable
  3. Money is Divisible
  4. Money is Fungible (exchangeable)
  5. Money is A Store of Value
If we examined the U.S. dollar or any other currency in the world which is backed only by confidence (fiat currency) we would quickly realize that none of these currencies function as a store of value. Case in point, I read an article recently about a couple that found many buried gold coins on their property. The total worth of the gold coins was around $10 million. The youngest minted coin found was from 1894. So imagine you buried $10,000 worth of cash in the ground today. Do you believe in over 100 years that cash will be worth equal to today's cash in terms of purchasing power? I believe its safe to say most people know that would not be the case. Gold and precious metals on the other hand have always maintained their value because of a very simple principle. It requires time and energy to get it. Humans cannot create gold or silver and therefore it is a finite resource which requires considerable effort to capture it. Can we say the same about government currencies? All that is needed to make U.S dollars is a printing press or a computer program with some authority behind it. So why do we use this government sponsored currency? The complete answer to that question requires a historical explanation beyond the scope of this article. Instead, lets examine Gold and Silver and why despite its advantages as a store a value it may not be the solution to a sound monetary system.

Gold coins were first struck as money dating back to 550 B.C. in Lydia. Over the course of the centuries, Gold and Silver were used as money. Soon though, governments began to reduce the purity of gold and silver with other metals more readily available. Over time, this eventually lead to the collapse of economies as their money became worthless and people became less and less likely to take these diluted forms of money.

Fast forward to today. Within the past 100 years our economic system has collapsed three times with another collapse fast approaching, according to many financial experts. The difference between the previous three collapses and the upcoming one is that the U.S. was able to benefit from the restructuring that took place which placed the U.S. dollar as the world reserve currency. For a more in-depth explanation of what these collapses looked like and how the U.S. was able to benefit, I highly recommend watching Mike Maloney's hidden secrets of money videos which can be found at

Today, the economic conditions are very different from 20 years ago. The price of every day goods and services is rising constantly. Gas and other forms of energy will also continue to rise in price. Why? Because similar to the way ancient governments would dilute their gold and silver money with common metals the current global governments (especially the U.S.) are increasing the money supply of paper currency by printing massive amounts of money. The problem is even worse than that. The entire fiat currency system is predicated on the fact that U.S. dollars are borrowed into existence (more on that in Mike Maloney's videos) and therefore any debt accrued is mathematically impossible to pay off. The result can only be a systemic failure of the entire global economic system. However, as I mentioned before, this is not without precedent and is not meant to be taken as a dooms day scenario even though that is a possibility on the spectrum of possibilities. What will most likely happen is a new system will agreed upon by the world powers. This will not be without some calamity and destruction of U.S. dollar purchasing power.

This is where Bitcoin comes in. Without getting too technical on how Bitcoin works, bitcoin and other cryptocurrencies are special in that they are not controlled by anyone. There is no central bank or government that decides on how much to print/create. Just like gold and silver, energy and time must be allocated to mining cryptocurrencies through the use of computers. If the cryptocurrency (e.g. Bitcoin) you are using becomes accepted by enough businesses, users would not have to worry about:
  1. Money tracking by Government entities
  2. Taxes
  3. Inflation
The most important of these is arguably inflation. While inflation does not seem like a problem at the moment, we only have to think back to 2006-2008 when the gas prices nearly doubled to remember how disheartening it is on consumers. Whether you believe the U.S. is going to experience severe inflation or not, does not matter. If inflation does come to the U.S., many people will begin to scramble for a safe haven to store their wealth. While gold and silver function exceptionally well at this, they may not be as easily transferable as a digital currency. For this reason, Bitcoin may come to be widely accepted as an alternative to the U.S. dollar for transactions. As people look for stability and safety from a failing fiat currency system, Bitcoin might just be the solution. Because of Bitcoin's lack of government or central control, it might prove to be the invention that changes the very reality of people. It might very well be, the invention of true money.

The big question when it comes to Bitcoin is: will more businesses and producers of goods and services be willing to take bitcoin? I think the future economic environment will likely motivate more and more people to do so. Though, there is much the government can do to stop the ascent of Bitcoin. One possibility is to "back-up" the dollar with gold to restore confidence. This would basically set up the same situation where the governments could eventually print more than it actually has in gold to back it and start the fiat scam all over again. So the future of the United States and our economic freedom actually depends on whether cryptocurrencies come to be widely used. The only way that will happen is if people become educated on the topic of MONEY and what real money is. Whether this plays out for the benefit of mankind remains to be seen. One thing is certain, we live in exciting times.

Sunday, March 9, 2014

How does one become more self sufficient?

When you look at the political and economic landscape that we are living with, it doesn't take long before you realize its time for some self sufficiency and emergency preparedness. A major theme of my blog is going to focus on my personal experiences and methods to securing a prosperous future. One of my goals is to develop the skills and know-how for emergency situations or times of economic hardship.

Where do I start?

The best place to start is to identify what skills are most critical for emergency situations and what areas one is lacking in.

1. Health - Do you have physical and mental health? Being healthy and physically fit is obviously going to be a huge advantage during rough times.

2. Skills - What skills do you have to get you through a time when infrastructure fails? Do you know how to filter water? Do you know how to perform CPR? Do you know how to fix things? Can you defend yourself?

3. Tools - Do you have a bike to get somewhere if your car isn't working? Do you have the tools to fix things you use on a daily basis? 

4. Community - Do you know skilled people that can help you where you are weak? Do you know people who have your back in bad times?

5. Information - Do you  have the ability to acquire information? What if there is no internet access? Do you have books?

6. Energy - Can you produce your own energy, food or otherwise?

I think its important to be realistic when attempting to work on any objectives. You may never be 100% independent in any one category, but a person who is 5% independent is much better off than someone who is 0% independent. So pick a category and start working towards independance.

Saturday, January 26, 2013

Do States with Strict Gun Laws have Significantly Different Violent Crime Rates from States with Loose Gun Laws?

We are constantly hearing on the news that we need more gun control and that it would reduce gun violence. At first glance, it seems a reasonable assumption. For example, if you restrict how many people can own bats, its likely you would reduce the number of violent incidents involving a bat. 

But are we really trying to stop incidents of gun violence or are we interested in reducing violent crime in general? In other words, if reducing the number of guns available to the general public actually increased violent crime rate overall, or even had no effect on violent crime rate, would it make sense to ban guns? If we stop gun related suicides but have no impact on suicides overall, have we accomplished anything?

A lot of people will use statistics to convince you that something is good or bad without pointing to these limitations because it leads to questions that may have answers that go against what they want you to believe.

I don't want to portray myself as an unbiased researcher. On the contrary, I'd like to make sure you are aware of my biases and allow you to come to your own conclusion. In general, I do not believe gun laws are bad, when they do not punish law abiding citizens. However, I am mostly against any sort of restriction on access to semi-automatic firearms. My line of reasoning is that legal gun owners actually prevent crimes because criminals are less likely to commit a crime knowing that the person they are committing a crime against is very likely to use lethal force to defend them self. As a result, I'm interested in seeing what data indicate about the restriction of guns on crime rates.

The first thing I did was pull up a ranking of states by how strict they are in terms of gun laws.

This was taken from a website that is in favor of stricter gun laws: You can visit that website here.

Overall, you can find very misleading statements like "Many of the states with the strongest gun laws also have the lowest gun death rates nationwide."
While this may be true statistically, it doesn't say much about how these gun restrictions may impact overall crime rate. Its almost equivalent to banning or restricting cars and saying "By restricting cars, we've reduced the total number of car related deaths". Its easy to see that statements like this completely disregard other effects such a ban or restrictions may have on other things (like getting to work).

So once I collected this list of top 10's, I decided to find out how many violent crimes per 100,000 people were committed in each state. I chose this ratio because it would be unfair to compare states total number of violent crimes since they all vary in total population which is a very good predictor of total number of violent crimes (see my earlier post). In order to make a fair comparison, a ratio was necessary.

Next I plugged the data into SPSS. Here is the data:

1.00 Connecticut                 272.80
1.00 California                    411.10
1.00 New Jersey                   308.40
1.00 Massachusetts               428.40
1.00 Hawaii                             287.20
1.00 New York                   398.10
1.00 Maryland                   494.10
1.00 Illinois                        429.30
1.00 Rhode Island               247.50
1.00 Michigan                   445.30
2.00 South Dakota               254.10
2.00 Arizona                             405.90
2.00 Mississippi                 269.80
2.00 Vermont                     135.20
2.00 Louisiana                   555.30
2.00 Montana                     267.50
2.00 Wyoming                     219.30
2.00 Kentucky                   238.20
2.00 Kansas                     353.90
2.00 Oklahoma                   454.80

I grouped the states by Strictest (1) and Loosest (2). Next I checked to see if the data were normally distributed. This is important because if the data are not normally distributed, it violates an assumption that is necessary for doing a statistical test.

Under Sig, we can see the probability is greater than 10% for both groups, which means we can assume normality. Also, the t-tests are pretty robust even when the data are not normal. Meaning, if we violated this assumption we are only less likely to find a difference between the Strict and Loose group.

Next, I ran an independent samples t-test to analyze the data.

The data did not come out significantly different. Meaning, the number of violent crimes from a state with strict gun control was not significantly different from those that had loose gun control laws.

However, I noticed something interesting when I looked at the box-plots.

The dark line in the middle of the box is the average number of violent crimes in each group. Group 1 is the states with strict gun laws and group 2 is the states with loose gun laws. You'll notice from these plots that the average number of violent crimes is actually LOWER in group 2. Also, the little arms the stick out from the box indicate outliers (extreme values). If you look at the raw data I posted above, you'll notice there is one extreme state from group 2, Louisiana.

If Louisiana would have had an average number of violent crimes (or less), the states with loose gun laws would have actually had a significantly lower number of violent crimes. However, speculating how fudged data will affect conclusions could go the other way too.

Conclusion: Gun laws do not prevent or decrease violent crimes and may even increase them. Its important to question the statistics we are presented with because they are often misleading and frame things in a way that fail to take into account other things that should also be considered when passing legislation.

Personal opinion: Guns laws can be good. On the other hand, when you start punishing law abiding citizens for isolated incidents of gun violence, you are tossing the baby out with the bath water. Lowering crime rates and shootings requires educating the public and a conversation about mental health. Lets stop talking about guns as if they are the sole reason our society has tragic events.

Does Population Size Predict Violence?

During a recent discussion on gun control, an individual made a seemingly reasonable assumption that crime rate was influenced by population size. I didn't disagree with that assumption and my gut told me that it was probably true. However, I decided I needed more data before I could come to that conclusion.

The first thing I did was narrow down what type of behavior I wanted to look at. In this case, I wanted to look at Violent crimes. This is violent crimes as defined by the FBI:

In the FBI’s Uniform Crime Reporting (UCR) Program, violent crime is composed of four offenses: murder and nonnegligent manslaughter, forcible rape, robbery, and aggravated assault. Violent crimes are defined in the UCR Program as those offenses which involve force or threat of force.

Source: FBI Website

So now that I knew what I wanted to look at I needed data to analyze. I found the following data on another FBI Page.

This data had to be cleaned up to only include population and total number of violent crimes per state.

State Population # of Violent Crimes
     Connecticut            3,580,709                       9,767
     Maine            1,328,188                       1,636
     Massachusetts            6,587,536                     28,219
     New Hampshire            1,318,194                       2,478
     Rhode Island            1,051,302                       2,602
     Vermont               626,431                          847
     New Jersey            8,821,155                     27,203
     New York          19,465,197                     77,490
     Pennsylvania          12,742,886                     45,240
     Illinois          12,869,257                     55,247
     Indiana            6,516,922                     21,626
     Michigan            9,876,187                     43,983
     Ohio          11,544,951                     35,484
     Wisconsin            5,711,767                     13,532
     Iowa            3,062,309                       7,826
     Kansas            2,871,238                     10,162
     Minnesota3            5,344,861                     11,825
     Missouri            6,010,688                     26,889
     Nebraska            1,842,641                       4,665
     North Dakota               683,932                       1,689
     South Dakota               824,082                       2,094
     Delaware               907,135                       5,075
     District of Columbia4               617,996                       7,429
     Florida          19,057,542                     98,199
     Georgia            9,815,210                     36,634
     Maryland            5,828,289                     28,797
     North Carolina            9,656,401                     33,774
     South Carolina            4,679,230                     26,760
     Virginia            8,096,604                     15,923
     West Virginia            1,855,364                       5,861
     Alabama5            4,802,740                     20,174
     Kentucky            4,369,356                     10,406
     Mississippi            2,978,512                       8,036
     Tennessee            6,403,353                     38,944
     Arkansas            2,937,979                     14,129
     Louisiana            4,574,836                     25,406
     Oklahoma            3,791,508                     17,243
     Texas          25,674,681                   104,873
     Arizona            6,482,505                     26,311
     Colorado            5,116,796                     16,383
     Idaho            1,584,985                       3,184
     Montana5               998,199                       2,670
     Nevada            2,723,322                     15,309
     New Mexico            2,082,224                     11,817
     Utah            2,817,222                       5,494
     Wyoming               568,158                       1,246
     Alaska               722,718                       4,383
     California          37,691,912                   154,944
     Hawaii            1,374,810                       3,949
     Oregon            3,871,859                       9,586
     Washington            6,830,038                     20,121

Next, I copied this data over to SPSS which is a data analysis software. For those of you unfamiliar with SPSS and statistical analysis in general, think of it as software that helps you draw conclusions based off mathematical formulas. These analysis help you make probability statements (similar to weather predictions) to determine if there are relationships or differences.

I will be helping you (the reader) determine what we can conclude from the SPSS outputs.

Before I ran the analysis I was aware of certain limitations with these data. First, there are many things not being taken into account. To begin with, we aren't taking into account how many cities are in each state, the rate of poverty per state, amount of land, or other variables which could easily moderate any data and change the conclusions we draw from this given data set. Basically, we are working within limitations.

On to the analysis...

ANOVA Stands for Analysis of Variance. The important information from this table is the column all the way to the left under Sig. This stands for "significance". Basically what you can interpret from the .000 is that there is less than .01% chance that the population and number of violent crimes are not related.

Adjusted R Square is the value we want to look at in this table. Roughly what this translates to is that about 95% of violent crimes can be predicted by a change in population. When population increases, so too does the number of violent crimes. However, this does NOT mean that population increase CAUSES increases in violent crimes, only that you can predict an increase (with a very high degree of certainty in this case) in violent crimes.

I intend to analyze some more data soon. For example, I'd like to see how states with strict gun laws compare to states with less strict gun laws. This will take some time, stay tuned.