This is what happens when you tell women they're bad at math

Boy have I found a sexy economics paper to share with you all.

And by sexy I mean interesting, provocative, useful and upsetting. With a splash of Bayesian statistics. (why, what do you mean by sexy?). 

As is typical in economics, the authors have tried to hide its sex appeal with the title: A (Dynamic) Investigation of Stereotypes, Belief-Updating, and Behavior, by Katherine B. Coffman, Paola Ugalde Araya & Basit Zafar. But do not be fooled! 

What's the paper about?

This paper looks at how men and women update their beliefs and choices based on feedback on their verbal skills and maths. It addresses the gender gap in beliefs about skills, gender gaps in appetites for competition based on those skills, and the gender differences in how men and women change their beliefs and choices when they get feedback on their skills.

What's the big finding?

Here's the clanger because I don't believe in saving the conclusion until last: when women receive bad feedback, especially in math, they update their beliefs and choices more negatively than men do. They are also more likely to remember negative feedback in the future and let it guide their decisions.

As a grown woman with a complicated relationship with math, this hit hard. Math and I carry a lot of baggage. 

But let's go back a bit...how is the paper different from what we know already?

Here's the stuff that's already been established in previous literature:

• There's a gender gap in labour market outcomes, even amongst the highly skilled (and yeah, there's a whole pool of literature in what explains that gender gap which I won't get into).
• Women are less likely to major in high-earning STEM or business fields.
• Women are significantly less likely to opt into competitive tournaments than men, and growing evidence suggests men tend to be more over-confident than women on average.
• Providing feedback about performance can reduce gender gaps in competitive tournament entry in laboratory settings. But lab settings have tended to be one-off situations.
• When participants take an IQ test and receive feedback on their performance, one month later, beliefs are more responsive to positive than negative feedback, and positive feedback is more likely to be accurately recalled. 

What makes this study different from similar literature on gender gaps in beliefs and competitive choices:

• The authors investigate how the effects of feedback dissipate over time, and how the fade-out (if any) may depend on the stereotype of the domain (verbal abilities as a typically female domain and math as a typically male domain) and gender. 

So what did the study actually do?

I think I'm going to have to quote at length here, because I don't think my rewording can do this experiment justice. Here's a simple (I mean...simple is a relative concept here) explanation of what they study is trying to do:

Our experiment is inspired by many educational settings, where students take introductory courses in different domains, receive noisy feedback, and then decide what to specialize or compete in. We use a stylized, controlled environment to mimic important features of this setting, producing several advantages. 

First, we observe individual measures of ability in both domains. Second, we observe exogenous changes in the individual’s information set (which are quite hard to isolate in non-experimental settings), allowing us to cleanly study belief updating. Third, we have precise measures of beliefs. And, finally, we have well-defined measures of payoffs for the chosen domain as well as for the counterfactual domain - this offers us an advantage since counterfactual payoffs are, by definition, not observed in the field. 

Our design allows us to collect detailed information about beliefs, choices, and recall at different points in time in both a female and a male-typed domain. This allows us to ask whether there are differences across men and women and/or differences across the associated stereotype of the task. Thus, we present results in terms of two gender gaps: the male − female gap (average differences between men and women) and the gender-congruence gap (average differences between individuals in the gender-congruent domain and individuals in the gender-incongruent domain). Both gaps are potentially important for understanding gender disparities in educational and career settings of interest.

And in plain English? 

The experiment took place in two sessions, one week apart.

In the first session, participants (university age) take two assessment quizzes: one in math and one in verbal skills. Next, participants report their beliefs about their absolute (do they think they did well?) and relative performance (do they think they did well relative to their peers?) in each domain. The experimenters next inform participants that they will take a second round of quizzes one week later. 

Participants are then given a series of choices about how they would like to be compensated for their future performance in round 2. This is meant to measure choices around appetite for competition and pay-for-performance:

• First, they choose between being paid for math performance under a piece-rate scheme or for verbal performance under a piece-rate scheme ($1 per correct answer). This indicates their preferred domain.
• Next, the experimenters elicit participants' willingness-to-accept competition in each domain using price lists. Participants make a series of choices between receiving either $1 per correct answer in verbal (math) or entering a competitive pay scheme in math (verbal). The competitive option pays $X per correct answer in math (verbal) if they place in top the 40% of performers in the Round 2 math (verbal) quiz, but 0 otherwise. For each domain, we vary X from $1.5 to $4 across the rows. This indicates their willingness to compete with their peers.

Some participants then receive feedback about their relative performance (i.e. their performance relative to their peers). The peer reference group is randomly computer-generated, so the participant learns whether they performed better or worse than a random peer. Randomness is key here because the participant has no idea about average performance: they don't know if they got lucky or unlucky with the computer-drawn peer. So the information is useful, but noisy.

For half of the sample of participants who received feedback, the experimenters ask participants to update their beliefs about performance and choices (see above) again immediately after the receipt of this feedback. 

The other half of the sample that receives feedback leaves the first session without providing updated beliefs or choices. 

All participants return for the second session one week later. In the second session, participants share their beliefs and choices again, including those that did not receive feedback in the first session.

All participants then take the two Round 2 quizzes. Participants are also asked to recall the feedback they received in each domain at the end of the second session

What were the results?

Apart from the headline finding, here are some other interesting results:

• Men and women respond similarly to positive feedback if the have the same starting point, and they update their beliefs and choices similarly in response to positive feedback.
• The impact of bad news fades less over time than the impact of good news, particularly for women (relative to men) and for individuals who receive bad news in incongruent domains--women who receive bad news about their math skills, men who are bad at verbal skills-- (compared with congruent domains).
• Women's beliefs about their performance are more pessimistic than men's, and women are less willing to compete.
• Immediately after feedback, gender gaps are somewhat reduced, particularly for beliefs. However, in the week following feedback, gaps grow back toward their starting point. In particular, gender gaps in choices one week later are indistinguishable from gender gaps at baseline.
• The results are not driven by simply forgetting the feedback: 88% of feedback is accurately recalled one week later.

So to round it all up:

If we take a man and a woman with the same performance and the same initial beliefs, then provide the same bad news, the woman holds more pessimistic beliefs about herself one week later compared to the man. Similarly, even if we hold fixed performance and initial choices, women (compared to men) are less willing to compete one week after bad news. 

Now what?

As the authors allude to, these findings have implications for understanding how men and women might choose their fields of study, and subsequently, the gender ratios in certain domains and overall differences in labour market outcomes. 

I mean, this is just one study. It doesn't tell us the state of the universe. You'd need more studies looking into the same thing to know if we're really onto something here. 

But at the very least, I think this study helps us think about the multiple points where gender gaps can take place, emphasises the need to investigate how prior beliefs develop in the first place, and urges better thinking on how to cushion the long-lasting effects of negative feedback. 

I took a break, and now I'm back

So... I took a break from this blog. I didn't mean to. But leading up to lockdown, life got busy. And then during lockdown my brain got a little fuzzy and it's taken a while to get back into good habits. But I started this blog for a reason and it feels too early to give up on something without giving it my all. 

So this piece is me, trying to get things back on track. 

I'll start with a roundup of all the things I've been contemplating, reading and watching over the last two months (damn, how are we near the end of September??).

Stuff I read

Well, I read less than I have been for most of the year as my long term relationship with the library was put on hold and also, the aforementioned lockdown fuzzy brain. But the few books I did read were awesome and appropriate for my mood.

How to not die alone: The Surprising Science That Will Help You Find Love, Logan Ury

A somewhat bleak choice during lockdown. But I really enjoyed this book, and would happily recommend it to any single ladies out there because surely I'm not the only one on the planet in need of a little guidance.

How to not die alone is a very practical guide to dating and relationships, drawing on behavioural economics. Given I'm normally sceptical of both dating advice and behavioural economics, it's a miracle I'm such a fan (slight digression but...I think a lot of the instincts around behavioural economics are basically right and the approach is laudable but my gripe is that some people really stretch the conclusions and put way too much weight on theories that are sometimes based on shonky psych studies).

I loved the economics sprinkled throughout the book, and even though I remain sceptical of some of the studies (I cringed when the famously debunked 'paradox of choice' jam jar study was mentioned), I was willing to buy into many of the concepts. 

I also realised I've been an idiot by failing to conceive of the dating universe as just one big matching market. And as a Kiwi Indian over a certain age, my market's already thinner than others. And there are a bunch of other economic concepts that fell out of that: signaling, network effects, search costs, optimal stopping theory. I wish I'd done this analysis sooner. It seems so obvious now: the lowest cost, highest reward option for me right now is dating. 

Please look forward to my forthcoming paper on the economics of the dating market for Kiwi Indian women. I'm going to have to put in a lot more research.

Masala lab: The science of Indian cooking, Krish Ashok

This book was good! It's all about the science behind Indian cooking and why we cook things a certain way and in a certain order (and when it's OK to break the rules). It's almost disturbing how much I learned from this book. Why am I only now learning about how to layer flavours? Or that powdered spices are pretty much just aromatic sand (OK, I probably did know this one but have been too lazy prep my own masala and a part of me still wishes I didn't know the truth). It's a good book for younger generations who didn't grow up learning to cook the traditional way and absorbing all the basic instincts. It's also a good book if you're like me and feel that understanding the science behind something makes it even more wonderful (my appreciation of wine, for example, increased tenfold once I read about the science and geography behind it).

I think I'm going to have a lot of fun using the lessons from this book. One thing I took away from it is to treat your cooking like a science experiment: change one or two variables at a time to see how the final result fits with your preferences. I like this because it takes away the crushing disappointment of cooking a less-than-amazing dahl or curry because it's all just part of the experimentation process. Plus, experimenting helps with troubleshooting exactly when in the process the recipe went awry.

Year of yes, Shonda Rhimes

I picked this book up from the library after lockdown because I felt like I needed a bit of motivation. And I'm still thinking about it which makes it a good book and if it's a good book then I should make sure other people hear about it too. The premise of the book sounds a little corny: Shonda Rhimes, a highly successful and publicly acclaimed woman, commits to saying 'yes' to everything for entire year. Thankfully, the book's so much more than that. First, Shonda Rhimes is a beautiful and compelling (and funny!) writer so even if the content was bad it would've been a good read. Grey's Anatomy fans will love the Christina Yang references too. And this is the perfect book for introverts. Her descriptions of her once debilitating fear of public speaking vibed just a little too well. The main takeaway for me was just understanding a bit more around the default preferences of introverts and the importance of challenging those defaults sometimes.

Things I've been watching

I'm ashamed of how much Netflix I've managed to get through. And worse, how easily my brain slipped back into binge watching after years of training myself out of the habit. But it's done now, and I did discover some gems. This is a very abridged list.

Om Shanti Om

I wrote a whole roundup of excellent Indian films and didn't include Om Shanti Om. I've avoided this epitome of Bollywood for a long time because I assumed it would be too campy for my tastes. I won't lie. It's pretty campy. But also so, so good with a decent storyline to boot. Maybe chalk it up to lockdown, but I went into this film feeling pretty drained. But part-way through the film I found myself grinning. Actually grinning (yes, for those who have seen the film, it was during That Song). And I experienced this new and weird sensation which I think was pure joy? If you're new to Bollywood I recommend watching this after watching some of the big titles, as I think this is a film that rewards people who know their Bollywood. And if you're like me and have watched a bit of Bollywood but somehow skipped over this one, I implore you to correct this immediately.

Love is Blind

I got deeply invested in the relationships in this reality TV series and quickly developed reckons. The concept is about blind dates where couples "fall in love" without seeing each other, but the real juice comes with tracking their relationships when they can see each other and interact in the real world. Good escapism and incredibly binge-worthy.

The Bold Type

The series follows three millennial women working in the journalism industry. As a millennial woman myself, this hit all the right feels: career wins and struggles, having great mentors, the absolute beauty of female friendships, wokeism and not wokeism, and the highs and lows and grey areas of dating. 

Daughters of Destiny

Thank you, Netflix for giving me a little perspective. This is a documentary series about the Shanti Bhavan school in India which educates children from the 'untouchable' caste. I would have been perfectly satisfied with a documentary that talks about the importance of education for upward mobility in India, and the importance for girls in particular. But the documentary goes deeper in following the journeys of a set of girls through their education and home lives, and learning to straddle two very different worlds. That is, two very different worlds in India: the educated class and those who haven't had that opportunity. There was more than one 'oof' moment for me watching this series, and you find yourself rooting for those who are able to escape their circumstances while despairing for those left behind. As I said, this is a good watch for those needing a bit of perspective: this is why we fight for freedom and individual dignity.

The Mindy Project

This series needs no introduction or description, right? There are many episodes and I watched them all. 

Plans for the blog moving forward

No plans, as such. Except a conscious refocusing towards stuff that interests me or that I care about. If that happens to be policy or politics-related stuff then I know that it'll vibe with certain readers. But if what gets me back into the habit of writing happens to be roundups of my favourite Mindy Project episodes, then I guess we will all just have to deal with it. 

Emily Oster changed the way I think about economics

Perhaps in stark contrast to my last blog post, in this post I want to celebrate the good economics can do.

I have Eric Crampton to thank for introducing me to the wonderful work of Emily Oster. Oster's most famous book, Expecting Better: Why the Conventional Pregnancy Wisdom Is Wrong -- and What You Really Need to Know was a surprisingly engrossing read considering I have never been pregnant, have not been trying to get pregnant, and probably won't be getting pregnant anytime soon unless I end up birthing the next baby Jesus or something.

What I got out of Oster's book was a new appreciation of the economics. I learnt about the value economists can add in simply reading and evaluating the damn studies, and making sense of the data and evidence. You wouldn't think this is such a big deal. But as it turns out, in an area like pregnancy advice, it's clear that a lot of the time this just wasn't being done. And there are very real consequences. 'Conventional wisdom' based on bad studies or ignorance of better studies is everywhere when you start looking. 

Another value-add of Oster's work is that it is all about empowering individuals to think about risk and make decisions for themselves based on their risk preferences. This isn't just applicable to decisions related to pregnancy, although pregnancy turns out to be a really good example as the stakes are a lot higher and people may be a lot more risk averse than they would be otherwise. It's enabling individuals to make decisions related to their health and wellbeing, based on the best possible evidence, and knowledge of the stuff they still don't know (known unknowns). A little bit of data/evidence literacy can be a great thing!

Finally, because of my academic and career background, I tend to see economics and policy as inter-related. Obviously, this is a narrow view. There's a lot of economics that doesn't even touch on policy (and a whole lot of policy that willfully ignores economics!). But a lot of the most interesting and useful economics has to do with personal decision making: from finding a partner, to how to raise your children, to optimising your health and wellbeing, to deciding where to eat and where to live. In the absence of government telling you what to do at every stage of your life (I'm being optimistic about the future here), it helps to have analytical tools available. And economics is a very useful part of that toolkit.

Anyway, why am I talking about Emily Oster right now? Because Vox have published an excellent article on her and her career. Oster has been extremely prominent in the US media lately for her work on Covid-19 and reopening schools. As with almost any Covid-related topic, and Covid in the US in particular, the views have been considered controversial. Unsurprisingly, I recommend reading the whole thing. But here are some of the quotes I found most interesting:

“We’re facing basically this existential threat to schooling for all these kids, and public health,” she [Oster] remembers thinking, “and the best data that the CDC can marshal on this has been put together by a professor in her basement.” 

The story of how Oster has emerged as a singular authority on schools, despite her lack of a background in education policy or pandemic response, starts with an information vacuum.

This is why Oster reaches hero-status in my mind. It's easy to see an information gap and complain. Or wait for the government to get its act together. But whether you agree with her commentary and conclusions or not, the fact that individuals like her can see a massive information gap and work to fill it without access to the best resources available is worth celebrating. 

Oster says she doesn’t mind being criticized on the merits of her work, but she bristles at the notion that it’s not her place to talk about Covid-19 and schools.

 

“I find this credentialism frustrating because I think that it is an argument that people use to not bring multiple voices to a debate,” she says. “It’s absolutely true that there are a set of tools that come with epidemiology that I don’t have,” she adds. But she says she believes she has another set of tools — “thinking about risks and analyzing data and looking at evidence” — that are useful in their own right.

I think this sucks, and these attitudes prevail in NZ too. Sure, there were/are economists in NZ with bad takes on the pandemic. But that's not a reason to dismiss the analytical framework they can bring to the table. In an ideal world, epidemiology and economics would work together. But there seem to be people hell-bent on making this a war of the professions.

Oster’s trajectory over the last year is emblematic of the way a failure of federal leadership often left Americans rudderless, with seemingly nowhere to turn for guidance on life-or-death decisions. And now, as schools and the economy reopen and many are reevaluating their relationships to authority, data, and advice, Oster may be most relevant not for the times she’s tried to tell policymakers what to do, but for the times when she’s empowered people to make choices for themselves.

In the face of incompetent governments, people need the information that will help them make the best choices for themselves and their families. I'm grateful we didn't face the same problem here in NZ, but it's a lesson worth filing nonetheless: sometimes you cannot wait for the government to tell you what the right thing to do is.

Indeed, Oster is a cautious speaker — choosing her words meticulously, rarely showing emotion, unfailingly gracious to her critics.

This is who I want to be when I grow up. Too bad nearly all of these qualities are considered flaws generally, and more so when you're a woman.

Though she continued her academic work, she was increasingly seen publicly as a parenting expert (“She’s on the cover of Parenting Today; she’s not on the cover of The Economist,” Johnson notes).

Ah yes, because real economists are the crystal ball gazers and the ones who make complicated and fancy models that fail the real-world test. I'm not one to cry sexism for the hell of it. I'll let you make up your mind on that. 

Uh oh... are people only now learning economic forecasts are often wrong?

Is there a German word for the pleasure you experience when someone calls out economists who are consistently wrong? Because that's what I'm feeling. RNZ's piece on the problem with economists' forecasts reveals an issue that is not all that new, but people must have short memories. It's an issue that is dear to my heart. It's time to start calling economists out on their bad forecasts.

Full disclosure: I'm currently slowly making my way through Nate Silver's The Signal and the Noise: Why so many predictions fail -- but some don't. It's all about how to deal with uncertainty in forecasting. I'm enjoying it.

The problem with economists' forecasts is that they're often wrong. Embarrassingly wrong. 

The article gives economists a bit of a ribbing, and fair enough. But the fault doesn't wholly lie with economists -- they are after all dealing with multiple variables and layers of uncertainty attached to each. And economists presumably provide these forecasts because they're something the public and policymakers want to know. Forecasts are useful because policy responses can be slow: you really want to get your underground bunker built before the hurricane hits. Economic forecasts fill a necessary gap.

I could almost live with that, if the forecasts were delivered with appropriate humility and caveats. But often they're not -- or at least, the soundbites that make it to print do not reflect that. It's the over-confidence that bugs me. And while some of this may come down to naivety about the way media works, it's a little hard to swallow when many of these economists are seasoned media commentators.

There are also incentives at play. Economists are rewarded by the media for their grandiose predictions: they're the ones who get headlines, airtime and name recognition. By the time future events eventuate, the public memory of the exact forecast is long gone, all that remains is the memory that 'this economist said something smart on TV this one time'. The media too have an incentive to publish clear and confident forecasts: they make good soundbites. 

The RNZ article suggests the media include more caveats and disclaimers when broadcasting economists giving their forecasts. That would help. But we can go further.

Here are 3 things that I think would help incentivise better reporting of forecasts:

1) Have a public database of economists' past forecasts compared with the actual outcome. We already see a bit of this with political polling. Keeping a track record of economists' past claims has to be a good start to incentivising better commentary. Those with low confidence in their forecasts might be more reluctant to comment to media if they know they'll be held accountable. And it incentivises those who do talk to media to take more care with their claims. It's also a useful tool for the public to compare different takes and understand how forecasts stack up to reality.

2) Improve the supply-side of the equation. This is cribbed from the aforementioned Nate Silver book, who in turn references George Mason University economist Robin Hanson. Robin Hanson's recommendation is to use prediction markets, where the public can place bets on economic or policy outcomes. Hanson's insight is that there are simply very few incentives to produce good forecasts. By adding a real financial stake to forecasting, the incentives increase and shift away from just looking good to peers (e.g. being on TV and making headlines). An advantage of prediction markets is that they're dynamic: they can provide real-time information by being constantly updated when new information comes to light. Anyway, all of this sounds good and reasonable. But then I remember we don't have iPredict anymore in NZ so...there goes that idea.

3) Improve the demand-side of the equation: publish the margins of error, or confidence intervals, in forecasts. This is also cribbed from the Nate Silver book. The idea is to encourage the media and public to be better consumers of forecasts. Again, the public are already familiar with this format with political polling (whether they understand margins of error, I cannot comment). Good economists know and will admit that their forecasts carry a range of uncertainty. Being able to communicate that uncertainty is not only useful for the public, but is also fairer on the economists who should know and want to highlight the uncertainty of their forecasts.

Not all economists who make forecasts are bad, and not all forecasts are bad. What we need are better mechanisms for discerning which ones to take more seriously.

Fun things in the FPA briefings

A slew of Fair Pay Agreement (FPA)-related briefings were released last week, available at MBIE's document library. If you want to understand the complexity of the system, I recommend taking a look. There's a hell of a lot of good analysis in there.

The most important document released, the Regulatory Impact Statement (RIS), has already been covered in the media so I'm not going to rehash what has already been said. The gist, as Stuff reports, is that 'officials recommended scrapping Labour's Fair Pay Agreement plan and strengthening existing law' and the RIS highlights the significant risks and challenges with the system. Most importantly (and most damning) the RIS warns that the costs of the FPA system may outweigh the benefits. Turns out that free and frank advice isn't dead after all. You love to see it.

The briefings that were released had some fascinating bits too. The two pieces of advice that I found most interesting are: 

1) MBIE recommended a more targeted application of FPAs and pointed out the risks of not doing so; and 

2) if Business NZ hadn't agreed to be the default bargaining representative for employers then the next best option entailed significant risks to the FPA system.

MBIE recommended a more targeted application of FPAs

Remember when FPAs were sold to us as helping the poorest and most vulnerable workers in the labour market: the cleaners, security guards and supermarket workers? Unfortunately, the proposed initiation tests in the Cabinet paper for FPAs do not guarantee that these workers will be prioritised.

The threshold for what sectors/occupations get to initiate bargaining for an FPA are decided by initiation tests. Under the proposed system, the initiation test involves satisfying one of the following tests: 

1. A representation test, that would require at least 10% of the covered workforce or 1,000 employees in coverage to support initiation (whichever is lower), or 

2. A public interest test, that would require evidencing that an industry or occupation faces certain labour market issues, such that an FPA would be in the public interest. 

These thresholds seem extremely low: requiring only limited support from workers even when there is no evidence of labour market issues, and not requiring a mandate from workers if labour market issues are identified. 

But, it turns out that things didn't have to be this way. MBIE recommended having a narrower scope for FPAs and provided advice on the risks associated with the approach ultimately taken in the Cabinet paper. The previous Minister (partially) agreed to this. Here's MBIE's advice:

The briefing goes on to explain the risks of the Cabinet paper's approach of having a rather low and untargeted initiation test. First, it would make it more difficult to ensure priority for workers in sectors where there is a ‘race to the bottom’. This is pretty important if the point of the system is meant to be aimed at vulnerable and low paid workers. In fact, MBIE points out that it is the most coordinated, unionised sectors (say, in the public sector) are better placed to initiate an FPA, and could crowd out less resourced and organised sectors who are more in need. 

The lower initiation tests will also substantially increase the fiscal costs of the system. This is important given the RIS has already warned that there is a possibility that the FPA system may not produce net benefits. 

Finally, the untargeted approach makes it harder to justify the fact FPAs negatively affect human rights and international obligations. This is a biggie. The RIS covers this issues too:

Under MBIE's preferred approach, if FPAs were only able to be initiated in sectors where both tests were met, then maybe there'd be some justification for affecting human rights and international obligations. At least under MBIE's approach there'd be a stronger mandate from workers. I'm keen to see what advice comes out in the public submissions process on this point. 

What would happen if Business NZ refused to be the default employer representative?

This is a fun thing to consider: what if employers simply refused to participate in FPA bargaining? It's not really a crazy possibility, given how many employers have said they do not support the system. That's why securing BusinessNZ's agreement to be the default bargaining representative for employers if no one else steps up is so important (and yes, at the time of writing they have agreed). But I have wondered what would have happened if BusinessNZ had refused to participate in the FPA system. 

MBIE's briefing sheds some light on this. Here's the advice (excuse my bad snip and paste):

Just to reiterate although I think the advice is pretty clear: if BusinessNZ had refused to participate, the next best option has significant has significant risks, including the possibility of being legally challenged and departing from the core concept that FPAs are bargained.

The 'next best' option also comes down to how great an incentive it is to have a bargained outcome rather than a determined one. Remember, collective bargaining can be a messy and costly process. And there is still a risk of going to determination anyway if parties cannot agree. In fact, the RIS points out that:

"Although the outcome is difficult to predict we anticipate in many cases the system is likely to result in bargaining stalemates and determinations fixing terms by the Employment Relations Authority, so the added benefit of bargaining may be limited." 

So... going straight to determination may actually save both bargaining parties a lot of time and resources if they're likely to end up in a stalemate and determination further down the line. If this becomes an expectation, then there doesn't seem to be much incentive to participate in bargaining. 

Anyway, all of this is interesting because BusinessNZ have called for FPAs to be scrapped. So while the 'next best' option is currently moot, I'm filing it away in my memory palace just in case. 

To conclude, I must end with an apology: I am sorry if you got to the end of this and discovered there was nothing fun about the FPA briefings at all. For future reference, I'm the kind of person who gets a thrill out of organising my sock drawer. But even if you find FPAs hopelessly boring and complex (they are definitely the latter), the implications for freedom and the way we negotiate employment agreements in New Zealand are massive. And all this, without requiring any evidence of a real labour market problem. Boy am I looking forward to reading the submissions on this thing.