Why Australia is not becoming America, and the HECS system still works

I am sick of reading alarmist media coverage and facebook statuses proclaiming that Australia is becoming America. The people making these comments probably have little understanding or appreciation of the “student debt crisis” in America, or the key differences between the US system and the Australian system post 2014 budget.

 

In this post, I am not attempting to offer an opinion on whether the government’s deregulation of university fees is positive or negative overall. This is a very complex question, there are many unknowns, and even the experts disagree. What I will tell you is why I don't think the 2014 budget means that Australia is becoming America, and why we won't have some sort of student debt crisis in the future.

The first thing to note is that regardless of how high the loan balance is, HECS loans are only repayable as a percentage of income that you actually receive. That means if you are unemployed or a low income earner, you don’t pay anything.

The student loan market in the US is complicated and there are various types of loans available. Many of these loans are repayable regardless of employment status and amount earned. This has created issues with rising unemployment levels during the GFC – people lose their jobs and then default on student loan repayments. 

The most flexible loans in the US (federal loans) allow deferral of repayments in some circumstances, but those circumstances are not as generous as under the HECS system. Under HECS, if you don’t earn, you don’t pay. If you do earn, you only pay a percentage of your income, and this percentage starts off small and only rises as you earn more. In 2009, 31% of US graduates reported paying over 12% of their income in education debt repayments (Source). Currently in Australia, the maximum you’ll ever pay is 8% of your income and you have to be earning over $80k to do that!

The second thing to note is that in America, private loans are often taken out by students to finance the gap between the cost of education and federal student loan limits. Most often, these loans are offered by private institutions (ie banks) and they are much more expensive and less flexible than federal loans. 

The closest analogy in an Australian context is taking out a personal loan or home loan with an Australian bank. With these loans, the bank is taking on the risk of the loan, and although they might offer limited hardship relief, it won’t be long before they’ll enforce the security underlying the loan (ie, repossess your house or car or your parent’s house or car if they guaranteed your loan) if you default. Repayments are fixed regardless of how much you earn or whether you have a job. Interest rates are generally variable, which is a risk factor because they could rise substantially depending on the economy. The banks look out for themselves – they are for-profit institutions.

The vast majority of Australians would never consider taking out a personal loan to pay for their accommodation during university, let alone their tuition fees. In America, this is much more commonplace. 

Finally, let me say that we don’t know exactly what will happen to university fees now that they will be deregulated. Currently, the average ratio of student loans to income is much higher in the US than it is here, and that might change. Personally, I think the statement in this article that “universities will increase tuition fees to international student fee levels, which are currently about three times higher. The Group of Eight universities will do that pretty quickly” may be an exaggeration. 

Even if it isn’t, my simplistic thoughts on the matter are:

• If a degree costs 120k, people will be less likely to study one that is less likely to lead to a decent income and employment (I’m thinking an arts degree).
• People might get some experience in the workforce and start studying later, which can be very positive (I personally wish I’d done this for various reasons).
• If less people go to university, this would make it easier for graduates to find work. It might also over time push up salaries in careers requiring a degree.
• More people will consider TAFE and apprenticeships (and the Government’s 2014 budget measures to encourage these options and make them more financially viable are to be applauded). I personally think that too many people go to university when they would be more suited to doing a trade or TAFE course. We have skill shortages in some trades, and graduates of certain degrees can’t find a job because of oversupply. This imbalance needs to be corrected.

I don’t like how HECS interest will rise to cover the Government’s cost of lending, but I suppose it does encourage people to pay off their loan faster. Ultimately it reduces the cost to the Government of providing these loans, and there is scope for the Government to reduce the interest charge if that’s feasible down the track (wishful thinking…)  Yes it sucks, but like ever rising taxes, I think that we’ll grumble and then move on.

If I have gotten anything wildly wrong, as always, please comment and correct me!

Why Social Media is not just for Teens...

Facebook. Twitter. Myspace. Youtube. Linkedin. Bebo. Flickr. Blogger.

Social media is a marketer's dream. I'm not just talking about for advertising, this post is about stats. Statistics. Mathematics. Market research. Social and behavioural science. Stuff which fascinates me for some inexplicable reason.

Source: Digital Buzz

I had some interest in using social media for data mining, and so I did some research. I found that the capabilities already out there go well beyond what I imagined. Prepare to be gobsmacked:

• Companies can use Twitter to profile people by geography, sentiment, gender and more. For example, data mining using the term "cat lover" might reveal where best to set up a cat accessories store. This example is a bit left field, but you can see where I'm going with it. Clients from financial services, healthcare, retail, politics, TV and news media companies have started using social media to gain a better understanding of their industry. Twitter has proven to be a surprisingly accurate indicator of levels of influenza in the community (and so data mining could be useful for predicting epidemics, tracking contamination etc). It is an excellent tool for political analysis and may even be a predictor of stock market activity and volatility, or perhaps a trading strategy. 

• With Twitter Sentiment, anyone can search a brand and find out both positive and negative comments relating to it, as well as a graph depicting the percentages of positive vs negative sentiment. I did a few test searches and I'm not sure how accurate, or extensive this app is, but it's certainly a sign of things to come. Another tool, Twist, creates graphs of the frequency that a brand is mentioned at any given time during a day, month etc.

• Social networks are a goldmine for data for analysing behaviour and emotions. One study linked particular words with positive and negative moods. For example, posts using the word "awesome" or "fantastic" or "happy" would indicate a positive state, whereas words such as "angry" or "upset" would indicate a negative state. Obviously there is some scope for inaccuracy in an individual post, but once you mine large quantities of data you can observe interesting trends. They found that people tend to be happier in the morning and during weekends (no surprises there!). The messages revealed that people wake up happy and slowly grow more disgruntled and sour as the day goes on, though their affect usually rebounds in the evening (again, this makes sense!). You can see it here in graphical form.

• Did you know that Sydneysiders are the rudest Tweeters, followed by Brisbanites? Those in Adelaide are the most affectionate and those in Canberra the most aggressive and sad. No wonder I find Canberra somewhat depressing...

• Tweets or other posts provide a valuable time stamp, not only on moods but also behaviour. Marketers can use this sort of data to determine when best to target people with advertising, when to prompt people to buy and when to prompt them to share product information. For example, a UK analytics company did a study and found that pass-along value tweets are most frequently seen at 11:30am on Mondays, conversational tweets are heaviest on Tuesdays and news tweets are heaviest at 2:00pm on Tuesdays. I bet you didn't know that!

• Social networking offers endless posibilities for personality analysis and psychological profiling. Using Tweetstats, you can find out someone's most commonly used words (this is all about measuring the cognitive and emotional properties of a person based on the words they use). There are a number of other websites offering free personality analysis via your Twitter account. For those with the capabilities (such as analytics companies, marketing agencies and even the police if they invested in this sort of skill) you can see how a person's Facebook or Twitter account has the potential to provide a window into the person's mind. I envisage a crime show based on social media analysis, to find criminals and predict who a criminal's next victim will be...

•  If marketers want to target certain types of people, for example to seed a product, they can use a simple tool like Twitalyzer to find out a person's (a) Influence score, which is basically your popularity score on Twitter (b) signal-to-noise ratio (c) one's propensity to ‘retweet' or pass along others' tweets (d) velocity - the rate one's updates on Twitter and (e) clout - based on how many times one is cited in tweets. 

•  For people using Twitter as a publicity or marketing tool, TweetEffect analyses which tweets make them gain or loose followers. Obviously there are other factors at play so this app has limited accuracy, but a more accurate tool will no doubt emerge in the future. Other research reveals what types of tweets get re-tweeted most often, and what users can do to get more re-tweets.

•  Social media may even prove useful for companies to predict demand and control stock levels and manufacturing volumes. For example, they can find out if people like a newly released product, and how many intend to purchase it.

Some of above might seem obvious, but the point is that analysing data in this way may reveal some underlying and previously ignored trends and effects. In the book Supercrunchers: How Anything Can be Predicted, the author reveals some mind blowing ways that large data sets (such as social network posts) are used as predictors of future behaviour and how they are used to uncover cause and effect relationships. For example, casinos can calculate the maximum amount that a customer can lose and still come away feeling like they had a positive gambling experience thanks to a 'free' meal at the casino's restaurant. The blurb of this book asks the question: Why should you be worried if you are receiving good customer service? I definitely want to get my hands on it, it sounds fascinating, and worrying.

Is there anything about us that they won't know? Social media data analysis is a rapidly growing industry. Technology is rapidly changing the way that businesses operate, and well as the way we do business. Watch this space.

Source: Geeks are Sexy