"Panics do not destroy capital; they merely reveal the extent to which it has been previously destroyed by its betrayal into hopelessly unproductive works." John Stuart Mill
Perhaps. My advice... when dealing with raw medians, wait until you have several months of data before getting too excited.
Your advice would be no more than you can expect from a journalism cadet or an institutional brown noser. In the world of data analytics in 2015, the more raw the data, the better. This is why with schools such as MIT are teaching the opposite of what you are trained to think and read about data.
Why is this useful? The bigger the observations relative to aggregates, the far more interesting the data in respect to instability and predictive analytics. If the suburbanite observes that the 30% of house sales resulted in an outcome that is 84K lower than the previous month, they intuitively think "wow." And that is actually good, until it is explained away by people using rudimentary statistical techniques. Considering the power that we have to explore and crunch data properly, this is like living in the middle ages. It gets more ludicrous when house prices are falling more in a month that people make in a year.
house prices are falling more in a month that people make in a year
This is where your rudimentary understanding of statistics lets you down. You're 100% convinced that house prices really fell $84K in a month, but the truth is that prices may not have fallen at all. The composition of sales may simply have changed - i.e. mostly 2BR houses happened to sell last month, versus mostly 3BR houses the month before. The value of houses can actually rise, even if the raw median falls. For someone who claims to be a stats master, your comprehension is rather poor.
This is where your rudimentary understanding of statistics lets you down. You're 100% convinced that house prices really fell $84K in a month, but the truth is that prices may not have fallen at all. The composition of sales may simply have changed - i.e. mostly 2BR houses happened to sell last month, versus mostly 3BR houses the month before. The value of houses can actually rise, even if the raw median falls. For someone who claims to be a stats master, your comprehension is rather poor.
They did fall 84K in a month. No doubt about it.It's like a soap opera. S&P are strategically positioning. It always looks good.
"We believe that if a sharp fall in house prices in Auckland were to occur, most financial institutions in New Zealand will be adversely affected even when they do not have significant direct exposure to home lending in the city. This is because of the importance of Auckland to the New Zealand economy; it accounts for about 35% of the GDP and more than one-third of the country's population," says S&P.
"Additionally, we believe that a sharp decline in house prices in Auckland would likely be accompanied by weakening in other macroeconomic factors such as a slowdown in GDP and a rise in unemployment. The business and consumer sentiment is also likely to suffer as a result, in our opinion. Accentuating these risks are New Zealand economy's external weaknesses in our view. We expect that the credit losses of most New Zealand financial institutions will significantly increase in such a scenario."
So based on unstratified raw medians published by one organisation, you have no doubt that property in Central Auckland has dropped by $84K (10%) in a month. OK.
I assume then that you're equally trusting of the same data which shows an 8% jump in one month for Outer Auckland?
So based on unstratified raw medians published by one organisation, you have no doubt that property in Central Auckland has dropped by $84K (10%) in a month. OK.
I assume then that you're equally trusting of the same data which shows an 8% jump in one month for Outer Auckland?
It did. No doubt about it. Volatility makes it fascinating.
It did. No doubt about it. Volatility makes it fascinating.
if you are using the result only of a median you have no idea at all if prices fell. Computers and it being 2015 makes no difference at all. There is no way of providing an answer either way for a single calculation on a small sample.
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