Max Ghenis

Co-founder and CEO @ PolicyEngine
159 karmaJoined Dec 2016Working (15+ years)Washington, DC, USA



I'm the co-founder and CEO of PolicyEngine, a tech nonprofit that computes the impacts of public policy ( I'm also the founder and president of the UBI Center, a think tank researching universal basic income policies (

I first got into EA in 2012: I worked at Google at the time, and made a grant to GiveDirectly. I've since taken the GWWC pledge and focused my giving on GiveDirectly and GiveWell. I was active in Google's EA group and also MIT's when I went there for grad school in 2020.

I'm also the founder of Ventura County YIMBY, and a volunteer California state coordinator for Citizens' Climate Lobby, a grassroots organization advocating for a national carbon fee-and-dividend policy.


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Yeah both my cofounder Nikhil and I are longtime EAs :) We have a couple projects in the works on tying PolicyEngine to EA , which we'll probably launch in the next couple months.

Nikhil is actually in the UK as well (I'm in DC), so could you please connect him to the EAGx Cambridge folks? He's

You can also use PolicyEngine UK (my nonprofit's free, open source web app) to estimate your taxes and benefits given your income and household characteristics. It captures nuances like the Child Benefit High Income Tax Charge and phase-outs of Universal Credit and the Personal Allowance, and shows your total marginal tax rate considering these factors.

You can also design custom policy reforms, and PolicyEngine estimates the impact, both on the UK and your own household.

I'm all for this, though I've got a dog in the fight: I'm ED of PolicyEngine, a nonprofit that largely intends to improve epistemics around economic policymaking by making epistemic tech available to everyone. Our free, open source software estimates households' taxes and benefit eligibility, and lets users design customizable policy reforms and estimate impacts on society and households.

Since you mentioned a carbon tax, our new app, which we'll launch in January, lets you design a custom carbon tax in the UK. Here's a 2-minute video on how to do that and pair the carbon tax with a dividend, or the link directly to the policy. For example, we estimate that a budget neutral £100/ton carbon dividend would benefit 2/3 of UK residents and lower the poverty rate by 7%. We also model much of the US tax-benefit system, though we currently only model carbon taxes in the UK (here's how).

We'd be excited about building PolicyEngine into an educational initiative, especially with EAs. We've also started working on an EA Forum post for a shallow dive cost-effectiveness of computational policy simulation--I think this plays well into our community's embrace of forecasting as well. Happy to chat more with folks on this.

How many consumption-doublings does a policy reform generate?

GiveDirectly's unconditional cash transfers have long served as GiveWell's cost-effectiveness baseline. GiveWell's 2022 cost-effectiveness analysis estimates that GiveDirectly doubles the consumption of a person for a year for about $200. [1]

Tax and benefit reforms also affect households' consumption. My nonprofit, PolicyEngine, builds free open-source software that computes the impact of custom tax and benefit reforms on outcomes like poverty and the budget. This slide from my EAGxBerkeley lightning talk shows how we will display poverty impacts of a custom tax reform in our upcoming redesign.

My proposal is to add a chart to our app showing the impact of a policy reform on sum(ln(net income)), which could translate to total consumption-doublings for comparison with GiveDirectly. This could enable more data-driven EA-style advocacy for poverty-reducing policies. Currently we have models in the US and the UK, but we intend to expand to low- and middle-income countries in the future, and this visualization would translate to those new country models where reforms might be more cost-effective.

Here's our GitHub. Our stack is Python/Flask/React.

  1. ^

    Cell B87 shows that each philanthropic dollar spent generates 0.0034 units of value, which in this case is one-unit increases of ln(consumption). That is, it costs 1/0.0034=$294 to increase a person's ln(consumption) by one unit for a year. Doubling consumption for a year therefore costs $294 * ln(2) = $204.

My colleague Ahmed Ahmed and I summarized research on fertility in the context of the US Child Tax Credit expansion in this UBI Center report last year. We cited the Lyman Stone article from here:

Stone’s research suggests that making it permanent could close between 15% and 65% of the gap to a replacement fertility rate.

My nonprofit PolicyEngine has also been scoping how to predict fertility impacts in our app that computes the impact of custom tax and benefit reforms. Our shallow dive hasn't turned up standard elasticities with respect to current-year policy changes though, so while we could create ones like % change to births with respect to % change to net income of parents of newborns, I don't know how well this would connect well to the literature.

In general, though, Stone finds that baby bonuses are most cost-effective at spurring births. Other evidence suggests that reducing infant poverty improves developmental outcomes more cost-effectively than interventions later in life, and baby bonuses could be easily administered at any level of government (just run payments through the hospitals). In my view, that all makes baby bonuses an underexplored plausibly cost-effective intervention, both from a lobbying/policy perspective and through philanthropic means (a la GiveDirectly).

Really interesting post. Not to hijack it, but I didn't know about the EA Forecasting & Epistemics Slack. Can you point me to info on it or how to join?

Web app implementing giving pledges based on net income (after taxes and benefits)

The Giving What We Can Pledge is 10% of pre-tax income, if giving is tax-deductible, or 10% of post-tax income otherwise. We've scoped a different pledge, in which one gives the amount such that their net income after taxes and benefits falls 10%. You can also think of this as transferring 10% of your consumption to effective charity.

We propose building a web app where people enter their household information and it suggests the amount to give. The app would call the free, open source PolicyEngine API to compute taxes and benefits (I am the Executive Director of PolicyEngine, a nonprofit). I think in a day we can build a simple US prototype that collects a handful of data points (earnings, family size, state) and displays the computation.

I've discussed this idea with Luke Freeman, Executive Director of Giving What We Can, who supported experimenting with it.

We could cultivate for-profit entrepreneurship in fields with clearer social benefit. I've seen arguments that people can make a bigger impact by focusing on social impact or profitability rather than trying to do both, and I think that's true on the margin for most people, but embracing crypto may have overcorrected.

Thirdly, the question of whether going veg*n strengthens your altruistic motivations is an empirical one which I feel pretty uncertain about. There may well be a moral licensing effect where veg*ns feel (disproportionately) like they’ve done their fair share of altruistic action; or maybe parts of you will become resentful about these constraints. This probably varies a lot for different people.

Related to this is this study finding:

Across six experiments, including one conducted with individuals involved in policymaking, we show that introducing a green energy default nudge diminishes support for a carbon tax.

Makes sense and glad to see more EA centralization around Slack.

I might just suggest clarifying in this post that HIE is a community of physical engineers, as the website states.

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