Nepal has been captivated by cautious optimism following the electoral victory of Balendra Shah and the RSP, instilling a renewed sense of possibility in governance and the broader polity. However, this moment is a critical juncture: ensuring that this new era of alternative politics doesn’t make the same mistakes as the past—as governance is ultimately guided by the policies this upcoming government chooses to pursue.
RSP’s political campaign concentrated heavily on governance—drawing on citizen experiences with administrative staff, lapses in policy implementation, or overall vacuous policymaking. In the past, policy debates have centered around observable relationships—for example, how expedited transportation networks will lead to rapid economic growth. It’s understandable how this is appealing, we’re hardwired to identifying developed cities with clean and wide roads. However, places with pre-existing growth trends consistently attract better infrastructure, and as a result—better developed road networks. This ambiguity in causality is rarely acknowledged as we’ve stopped at observational correlation to apply a temporary band-aid—disregarding underlying issues.
This isn’t restricted to just road networks—policy debates have consistently centered around visible relationships—patterns that appear obvious but aren’t structurally understood. In most cases, cause and effect move both ways—we can’t isolate road networks from economic activity, nor the other way around. This ambiguity is further complicated by other underlying factors—affecting both transportation and economic networks. This form of misidentified causality ultimately fails to address policy targets and might even cause unintended negative externalities. This misidentification is not strictly an individual or political problem at the core—it’s simply about adjusting our approach to policymaking. We need to be able to establish clear causality in complex systems where observable relationships are not accounting for endogenous dynamics underneath. This can be done if policymaking is guided by thorough analysis: comparing regions with or without the policy, testing policies through randomized controlled trials (RCTs) before implementing broad scale reform and quantitatively tracking variance across implementation contexts. This will require recalibrating usual policymaking but will provide much higher returns on government effort and expenditure—resulting in effective outcomes and avoiding unintended harms.
This recalibrated policymaking can come into effect with our concerns over low exports—generally attributed to weak governance institutions or an unstable oversight mechanism. However, this relationship could very well run in the opposite direction—successful exporting industries or business communities could have instead led to the development of strong institutions and increased oversight to guarantee quality. Policymakers are challenged to distinguish between these explanations. Here is where government policies need to avoid blanket approaches and check for sectoral variation, difference-in-differences with policies already in place, and natural quasi-experimental variation with untreated regions. The results will allow policymakers to understand what actually drives exports, avoid allocating resources to unfocused reforms, and focus on interventions that actually improve export performance.
This strategy needs to expand well beyond export policy—observable outcomes in society are a result of broader equilibria shaped by interacting forces, and bad policy has often reinforced these underlying equilibria. We have consistently chased after symptoms instead of addressing root causes—what we observe are outcomes, not explanations. This political moment provides us with an opportunity to change this approach—a critical juncture as to how we decide to move forward.
The RSP has made efficient governance and expert policymaking a core electoral tenet—raising both opportunity and expectations from these new political actors. Our policies have largely been concentrated around observable relationships and unclear causality—an issue that isn’t fixed just by better policy design, but rather by a better understanding of what drives outcomes. The success of this electoral shift will depend not just on new policies, but rather on how carefully the outcomes of these new policies are understood.
